arxiv_id float64 1.5k 2.51k | title stringlengths 9 178 ⌀ | authors stringlengths 2 22.8k | categories stringlengths 4 146 | summary stringlengths 103 1.92k ⌀ | published stringdate 2015-02-06 10:44:00 2025-07-10 17:59:58 ⌀ | comments stringlengths 2 417 ⌀ | journal_ref stringclasses 321
values | doi stringclasses 398
values | ss_title stringlengths 8 159 ⌀ | ss_authors stringlengths 11 8.38k ⌀ | ss_year float64 2.02k 2.03k ⌀ | ss_venue stringclasses 281
values | ss_citationCount float64 0 134k ⌀ | ss_referenceCount float64 0 429 ⌀ | ss_fieldsOfStudy stringclasses 47
values |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1,803.08664 | Fast, Accurate, and Lightweight Super-Resolution with Cascading Residual
Network | ['Namhyuk Ahn', 'Byungkon Kang', 'Kyung-Ah Sohn'] | ['cs.CV'] | In recent years, deep learning methods have been successfully applied to
single-image super-resolution tasks. Despite their great performances, deep
learning methods cannot be easily applied to real-world applications due to the
requirement of heavy computation. In this paper, we address this issue by
proposing an accu... | 2018-03-23T06:07:20Z | European Conference on Computer Vision (ECCV), 2018 | null | null | null | null | null | null | null | null | null |
1,803.0901 | Datasheets for Datasets | ['Timnit Gebru', 'Jamie Morgenstern', 'Briana Vecchione', 'Jennifer Wortman Vaughan', 'Hanna Wallach', 'Hal Daumé III', 'Kate Crawford'] | ['cs.DB', 'cs.AI', 'cs.LG'] | The machine learning community currently has no standardized process for
documenting datasets, which can lead to severe consequences in high-stakes
domains. To address this gap, we propose datasheets for datasets. In the
electronics industry, every component, no matter how simple or complex, is
accompanied with a datas... | 2018-03-23T23:22:18Z | Published in CACM in December, 2021 | null | null | null | null | null | null | null | null | null |
1,803.09337 | Text Segmentation as a Supervised Learning Task | ['Omri Koshorek', 'Adir Cohen', 'Noam Mor', 'Michael Rotman', 'Jonathan Berant'] | ['cs.CL'] | Text segmentation, the task of dividing a document into contiguous segments
based on its semantic structure, is a longstanding challenge in language
understanding. Previous work on text segmentation focused on unsupervised
methods such as clustering or graph search, due to the paucity in labeled data.
In this work, we ... | 2018-03-25T20:53:40Z | 5 pages, 1 figure, NAACL 2018 | null | null | null | null | null | null | null | null | null |
1,803.11175 | Universal Sentence Encoder | ['Daniel Cer', 'Yinfei Yang', 'Sheng-yi Kong', 'Nan Hua', 'Nicole Limtiaco', 'Rhomni St. John', 'Noah Constant', 'Mario Guajardo-Cespedes', 'Steve Yuan', 'Chris Tar', 'Yun-Hsuan Sung', 'Brian Strope', 'Ray Kurzweil'] | ['cs.CL'] | We present models for encoding sentences into embedding vectors that
specifically target transfer learning to other NLP tasks. The models are
efficient and result in accurate performance on diverse transfer tasks. Two
variants of the encoding models allow for trade-offs between accuracy and
compute resources. For both ... | 2018-03-29T17:43:03Z | 7 pages; fixed module URL in Listing 1 | null | null | Universal Sentence Encoder | ['Daniel Matthew Cer', 'Yinfei Yang', 'Sheng-yi Kong', 'Nan Hua', 'Nicole Limtiaco', 'Rhomni St. John', 'Noah Constant', 'Mario Guajardo-Cespedes', 'Steve Yuan', 'C. Tar', 'Yun-Hsuan Sung', 'B. Strope', 'R. Kurzweil'] | 2,018 | arXiv.org | 1,908 | 27 | ['Computer Science'] |
1,804.00015 | ESPnet: End-to-End Speech Processing Toolkit | ['Shinji Watanabe', 'Takaaki Hori', 'Shigeki Karita', 'Tomoki Hayashi', 'Jiro Nishitoba', 'Yuya Unno', 'Nelson Enrique Yalta Soplin', 'Jahn Heymann', 'Matthew Wiesner', 'Nanxin Chen', 'Adithya Renduchintala', 'Tsubasa Ochiai'] | ['cs.CL'] | This paper introduces a new open source platform for end-to-end speech
processing named ESPnet. ESPnet mainly focuses on end-to-end automatic speech
recognition (ASR), and adopts widely-used dynamic neural network toolkits,
Chainer and PyTorch, as a main deep learning engine. ESPnet also follows the
Kaldi ASR toolkit s... | 2018-03-30T18:09:39Z | null | null | null | ESPnet: End-to-End Speech Processing Toolkit | ['Shinji Watanabe', 'Takaaki Hori', 'Shigeki Karita', 'Tomoki Hayashi', 'Jiro Nishitoba', 'Y. Unno', 'Nelson Yalta', 'Jahn Heymann', 'Matthew Wiesner', 'Nanxin Chen', 'Adithya Renduchintala', 'Tsubasa Ochiai'] | 2,018 | Interspeech | 1,515 | 46 | ['Computer Science'] |
1,804.00097 | Adversarial Attacks and Defences Competition | ['Alexey Kurakin', 'Ian Goodfellow', 'Samy Bengio', 'Yinpeng Dong', 'Fangzhou Liao', 'Ming Liang', 'Tianyu Pang', 'Jun Zhu', 'Xiaolin Hu', 'Cihang Xie', 'Jianyu Wang', 'Zhishuai Zhang', 'Zhou Ren', 'Alan Yuille', 'Sangxia Huang', 'Yao Zhao', 'Yuzhe Zhao', 'Zhonglin Han', 'Junjiajia Long', 'Yerkebulan Berdibekov', 'Taku... | ['cs.CV', 'cs.CR', 'cs.LG', 'stat.ML'] | To accelerate research on adversarial examples and robustness of machine
learning classifiers, Google Brain organized a NIPS 2017 competition that
encouraged researchers to develop new methods to generate adversarial examples
as well as to develop new ways to defend against them. In this chapter, we
describe the struct... | 2018-03-31T00:52:20Z | 36 pages, 10 figures | null | null | null | null | null | null | null | null | null |
1,804.02767 | YOLOv3: An Incremental Improvement | ['Joseph Redmon', 'Ali Farhadi'] | ['cs.CV'] | We present some updates to YOLO! We made a bunch of little design changes to
make it better. We also trained this new network that's pretty swell. It's a
little bigger than last time but more accurate. It's still fast though, don't
worry. At 320x320 YOLOv3 runs in 22 ms at 28.2 mAP, as accurate as SSD but
three times f... | 2018-04-08T22:27:57Z | Tech Report | null | null | YOLOv3: An Incremental Improvement | ['Joseph Redmon', 'Ali Farhadi'] | 2,018 | arXiv.org | 21,611 | 20 | ['Computer Science'] |
1,804.02815 | Recovering Realistic Texture in Image Super-resolution by Deep Spatial
Feature Transform | ['Xintao Wang', 'Ke Yu', 'Chao Dong', 'Chen Change Loy'] | ['cs.CV'] | Despite that convolutional neural networks (CNN) have recently demonstrated
high-quality reconstruction for single-image super-resolution (SR), recovering
natural and realistic texture remains a challenging problem. In this paper, we
show that it is possible to recover textures faithful to semantic classes. In
particul... | 2018-04-09T04:57:06Z | This work is accepted in CVPR 2018. Our project page is
http://mmlab.ie.cuhk.edu.hk/projects/SFTGAN/ | null | null | null | null | null | null | null | null | null |
1,804.03209 | Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition | ['Pete Warden'] | ['cs.CL', 'cs.HC'] | Describes an audio dataset of spoken words designed to help train and
evaluate keyword spotting systems. Discusses why this task is an interesting
challenge, and why it requires a specialized dataset that is different from
conventional datasets used for automatic speech recognition of full sentences.
Suggests a methodo... | 2018-04-09T19:58:17Z | null | null | null | Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition | ['Pete Warden'] | 2,018 | arXiv.org | 1,631 | 19 | ['Computer Science'] |
1,804.04235 | Adafactor: Adaptive Learning Rates with Sublinear Memory Cost | ['Noam Shazeer', 'Mitchell Stern'] | ['cs.LG', 'cs.AI', 'stat.ML'] | In several recently proposed stochastic optimization methods (e.g. RMSProp,
Adam, Adadelta), parameter updates are scaled by the inverse square roots of
exponential moving averages of squared past gradients. Maintaining these
per-parameter second-moment estimators requires memory equal to the number of
parameters. For ... | 2018-04-11T21:42:32Z | null | null | null | null | null | null | null | null | null | null |
1,804.05685 | A Discourse-Aware Attention Model for Abstractive Summarization of Long
Documents | ['Arman Cohan', 'Franck Dernoncourt', 'Doo Soon Kim', 'Trung Bui', 'Seokhwan Kim', 'Walter Chang', 'Nazli Goharian'] | ['cs.CL'] | Neural abstractive summarization models have led to promising results in
summarizing relatively short documents. We propose the first model for
abstractive summarization of single, longer-form documents (e.g., research
papers). Our approach consists of a new hierarchical encoder that models the
discourse structure of a... | 2018-04-16T13:55:20Z | NAACL HLT 2018 | null | null | null | null | null | null | null | null | null |
1,804.05938 | Unbiased Learning to Rank with Unbiased Propensity Estimation | ['Qingyao Ai', 'Keping Bi', 'Cheng Luo', 'Jiafeng Guo', 'W. Bruce Croft'] | ['cs.IR'] | Learning to rank with biased click data is a well-known challenge. A variety
of methods has been explored to debias click data for learning to rank such as
click models, result interleaving and, more recently, the unbiased
learning-to-rank framework based on inverse propensity weighting. Despite their
differences, most... | 2018-04-16T21:03:07Z | null | null | 10.1145/3209978.3209986 | null | null | null | null | null | null | null |
1,804.06437 | Delete, Retrieve, Generate: A Simple Approach to Sentiment and Style
Transfer | ['Juncen Li', 'Robin Jia', 'He He', 'Percy Liang'] | ['cs.CL'] | We consider the task of text attribute transfer: transforming a sentence to
alter a specific attribute (e.g., sentiment) while preserving its
attribute-independent content (e.g., changing "screen is just the right size"
to "screen is too small"). Our training data includes only sentences labeled
with their attribute (e... | 2018-04-17T18:59:51Z | NAACL 2018 | null | null | null | null | null | null | null | null | null |
1,804.06876 | Gender Bias in Coreference Resolution: Evaluation and Debiasing Methods | ['Jieyu Zhao', 'Tianlu Wang', 'Mark Yatskar', 'Vicente Ordonez', 'Kai-Wei Chang'] | ['cs.CL', 'cs.AI'] | We introduce a new benchmark, WinoBias, for coreference resolution focused on
gender bias. Our corpus contains Winograd-schema style sentences with entities
corresponding to people referred by their occupation (e.g. the nurse, the
doctor, the carpenter). We demonstrate that a rule-based, a feature-rich, and a
neural co... | 2018-04-18T18:51:00Z | NAACL '18 Camera Ready | null | null | null | null | null | null | null | null | null |
1,804.07461 | GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language
Understanding | ['Alex Wang', 'Amanpreet Singh', 'Julian Michael', 'Felix Hill', 'Omer Levy', 'Samuel R. Bowman'] | ['cs.CL'] | For natural language understanding (NLU) technology to be maximally useful,
both practically and as a scientific object of study, it must be general: it
must be able to process language in a way that is not exclusively tailored to
any one specific task or dataset. In pursuit of this objective, we introduce
the General ... | 2018-04-20T06:35:04Z | ICLR 2019; https://gluebenchmark.com/ | null | null | GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding | ['Alex Wang', 'Amanpreet Singh', 'Julian Michael', 'Felix Hill', 'Omer Levy', 'Samuel R. Bowman'] | 2,018 | BlackboxNLP@EMNLP | 7,215 | 77 | ['Computer Science'] |
1,804.07927 | DuoRC: Towards Complex Language Understanding with Paraphrased Reading
Comprehension | ['Amrita Saha', 'Rahul Aralikatte', 'Mitesh M. Khapra', 'Karthik Sankaranarayanan'] | ['cs.CL'] | We propose DuoRC, a novel dataset for Reading Comprehension (RC) that
motivates several new challenges for neural approaches in language
understanding beyond those offered by existing RC datasets. DuoRC contains
186,089 unique question-answer pairs created from a collection of 7680 pairs of
movie plots where each pair ... | 2018-04-21T09:43:06Z | Accepted in ACL 2018 | null | null | null | null | null | null | null | null | null |
1,804.09301 | Gender Bias in Coreference Resolution | ['Rachel Rudinger', 'Jason Naradowsky', 'Brian Leonard', 'Benjamin Van Durme'] | ['cs.CL'] | We present an empirical study of gender bias in coreference resolution
systems. We first introduce a novel, Winograd schema-style set of minimal pair
sentences that differ only by pronoun gender. With these "Winogender schemas,"
we evaluate and confirm systematic gender bias in three publicly-available
coreference reso... | 2018-04-25T00:46:14Z | Accepted to NAACL-HLT 2018 | null | null | Gender Bias in Coreference Resolution | ['Rachel Rudinger', 'Jason Naradowsky', 'Brian Leonard', 'Benjamin Van Durme'] | 2,018 | North American Chapter of the Association for Computational Linguistics | 646 | 27 | ['Computer Science'] |
1,804.10959 | Subword Regularization: Improving Neural Network Translation Models with
Multiple Subword Candidates | ['Taku Kudo'] | ['cs.CL'] | Subword units are an effective way to alleviate the open vocabulary problems
in neural machine translation (NMT). While sentences are usually converted into
unique subword sequences, subword segmentation is potentially ambiguous and
multiple segmentations are possible even with the same vocabulary. The question
address... | 2018-04-29T16:13:44Z | Accepted as a long paper at ACL2018 | null | null | null | null | null | null | null | null | null |
1,804.11283 | Newsroom: A Dataset of 1.3 Million Summaries with Diverse Extractive
Strategies | ['Max Grusky', 'Mor Naaman', 'Yoav Artzi'] | ['cs.CL'] | We present NEWSROOM, a summarization dataset of 1.3 million articles and
summaries written by authors and editors in newsrooms of 38 major news
publications. Extracted from search and social media metadata between 1998 and
2017, these high-quality summaries demonstrate high diversity of summarization
styles. In particu... | 2018-04-30T15:53:05Z | Proceedings of NAACL-HLT 2018 (Long Paper) | null | null | Newsroom: A Dataset of 1.3 Million Summaries with Diverse Extractive Strategies | ['Max Grusky', 'Mor Naaman', 'Yoav Artzi'] | 2,018 | North American Chapter of the Association for Computational Linguistics | 559 | 35 | ['Computer Science'] |
1,805.00123 | CrowdHuman: A Benchmark for Detecting Human in a Crowd | ['Shuai Shao', 'Zijian Zhao', 'Boxun Li', 'Tete Xiao', 'Gang Yu', 'Xiangyu Zhang', 'Jian Sun'] | ['cs.CV'] | Human detection has witnessed impressive progress in recent years. However,
the occlusion issue of detecting human in highly crowded environments is far
from solved. To make matters worse, crowd scenarios are still under-represented
in current human detection benchmarks. In this paper, we introduce a new
dataset, calle... | 2018-04-30T22:49:54Z | null | null | null | CrowdHuman: A Benchmark for Detecting Human in a Crowd | ['Shuai Shao', 'Zijian Zhao', 'Boxun Li', 'Tete Xiao', 'Gang Yu', 'Xiangyu Zhang', 'Jian Sun'] | 2,018 | arXiv.org | 689 | 33 | ['Computer Science'] |
1,805.00932 | Exploring the Limits of Weakly Supervised Pretraining | ['Dhruv Mahajan', 'Ross Girshick', 'Vignesh Ramanathan', 'Kaiming He', 'Manohar Paluri', 'Yixuan Li', 'Ashwin Bharambe', 'Laurens van der Maaten'] | ['cs.CV'] | State-of-the-art visual perception models for a wide range of tasks rely on
supervised pretraining. ImageNet classification is the de facto pretraining
task for these models. Yet, ImageNet is now nearly ten years old and is by
modern standards "small". Even so, relatively little is known about the
behavior of pretraini... | 2018-05-02T17:57:16Z | Technical report | null | null | null | null | null | null | null | null | null |
1,805.01978 | Unsupervised Feature Learning via Non-Parametric Instance-level
Discrimination | ['Zhirong Wu', 'Yuanjun Xiong', 'Stella Yu', 'Dahua Lin'] | ['cs.CV', 'cs.LG'] | Neural net classifiers trained on data with annotated class labels can also
capture apparent visual similarity among categories without being directed to
do so. We study whether this observation can be extended beyond the
conventional domain of supervised learning: Can we learn a good feature
representation that captur... | 2018-05-05T00:47:01Z | CVPR 2018 spotlight paper. Code:
https://github.com/zhirongw/lemniscate.pytorch | null | null | null | null | null | null | null | null | null |
1,805.0241 | MMDenseLSTM: An efficient combination of convolutional and recurrent
neural networks for audio source separation | ['Naoya Takahashi', 'Nabarun Goswami', 'Yuki Mitsufuji'] | ['cs.SD', 'eess.AS'] | Deep neural networks have become an indispensable technique for audio source
separation (ASS). It was recently reported that a variant of CNN architecture
called MMDenseNet was successfully employed to solve the ASS problem of
estimating source amplitudes, and state-of-the-art results were obtained for
DSD100 dataset. ... | 2018-05-07T09:18:25Z | null | null | null | null | null | null | null | null | null | null |
1,805.04833 | Hierarchical Neural Story Generation | ['Angela Fan', 'Mike Lewis', 'Yann Dauphin'] | ['cs.CL'] | We explore story generation: creative systems that can build coherent and
fluent passages of text about a topic. We collect a large dataset of 300K
human-written stories paired with writing prompts from an online forum. Our
dataset enables hierarchical story generation, where the model first generates
a premise, and th... | 2018-05-13T07:07:08Z | null | null | null | null | null | null | null | null | null | null |
1,805.08318 | Self-Attention Generative Adversarial Networks | ['Han Zhang', 'Ian Goodfellow', 'Dimitris Metaxas', 'Augustus Odena'] | ['stat.ML', 'cs.LG'] | In this paper, we propose the Self-Attention Generative Adversarial Network
(SAGAN) which allows attention-driven, long-range dependency modeling for image
generation tasks. Traditional convolutional GANs generate high-resolution
details as a function of only spatially local points in lower-resolution
feature maps. In ... | 2018-05-21T23:10:35Z | null | null | null | null | null | null | null | null | null | null |
1,805.08949 | Learning to Mine Aligned Code and Natural Language Pairs from Stack
Overflow | ['Pengcheng Yin', 'Bowen Deng', 'Edgar Chen', 'Bogdan Vasilescu', 'Graham Neubig'] | ['cs.CL', 'cs.SE'] | For tasks like code synthesis from natural language, code retrieval, and code
summarization, data-driven models have shown great promise. However, creating
these models require parallel data between natural language (NL) and code with
fine-grained alignments. Stack Overflow (SO) is a promising source to create
such a d... | 2018-05-23T03:39:04Z | MSR '18 | null | null | null | null | null | null | null | null | null |
1,805.09501 | AutoAugment: Learning Augmentation Policies from Data | ['Ekin D. Cubuk', 'Barret Zoph', 'Dandelion Mane', 'Vijay Vasudevan', 'Quoc V. Le'] | ['cs.CV', 'cs.LG', 'stat.ML'] | Data augmentation is an effective technique for improving the accuracy of
modern image classifiers. However, current data augmentation implementations
are manually designed. In this paper, we describe a simple procedure called
AutoAugment to automatically search for improved data augmentation policies. In
our implement... | 2018-05-24T04:05:42Z | CVPR 2019 | null | null | null | null | null | null | null | null | null |
1,805.12471 | Neural Network Acceptability Judgments | ['Alex Warstadt', 'Amanpreet Singh', 'Samuel R. Bowman'] | ['cs.CL'] | This paper investigates the ability of artificial neural networks to judge
the grammatical acceptability of a sentence, with the goal of testing their
linguistic competence. We introduce the Corpus of Linguistic Acceptability
(CoLA), a set of 10,657 English sentences labeled as grammatical or
ungrammatical from publish... | 2018-05-31T13:52:06Z | null | null | null | null | null | null | null | null | null | null |
1,806.00926 | NRTR: A No-Recurrence Sequence-to-Sequence Model For Scene Text
Recognition | ['Fenfen Sheng', 'Zhineng Chen', 'Bo Xu'] | ['cs.CV'] | Scene text recognition has attracted a great many researches due to its
importance to various applications. Existing methods mainly adopt recurrence or
convolution based networks. Though have obtained good performance, these
methods still suffer from two limitations: slow training speed due to the
internal recurrence o... | 2018-06-04T02:10:35Z | 6 pages, 3 figures, 3 tables | null | null | null | null | null | null | null | null | null |
1,806.02847 | A Simple Method for Commonsense Reasoning | ['Trieu H. Trinh', 'Quoc V. Le'] | ['cs.AI', 'cs.CL', 'cs.LG'] | Commonsense reasoning is a long-standing challenge for deep learning. For
example, it is difficult to use neural networks to tackle the Winograd Schema
dataset (Levesque et al., 2011). In this paper, we present a simple method for
commonsense reasoning with neural networks, using unsupervised learning. Key to
our metho... | 2018-06-07T18:13:08Z | null | null | null | null | null | null | null | null | null | null |
1,806.03822 | Know What You Don't Know: Unanswerable Questions for SQuAD | ['Pranav Rajpurkar', 'Robin Jia', 'Percy Liang'] | ['cs.CL'] | Extractive reading comprehension systems can often locate the correct answer
to a question in a context document, but they also tend to make unreliable
guesses on questions for which the correct answer is not stated in the context.
Existing datasets either focus exclusively on answerable questions, or use
automatically... | 2018-06-11T06:10:11Z | ACL 2018 | null | null | null | null | null | null | null | null | null |
1,806.04558 | Transfer Learning from Speaker Verification to Multispeaker
Text-To-Speech Synthesis | ['Ye Jia', 'Yu Zhang', 'Ron J. Weiss', 'Quan Wang', 'Jonathan Shen', 'Fei Ren', 'Zhifeng Chen', 'Patrick Nguyen', 'Ruoming Pang', 'Ignacio Lopez Moreno', 'Yonghui Wu'] | ['cs.CL', 'cs.LG', 'cs.SD', 'eess.AS'] | We describe a neural network-based system for text-to-speech (TTS) synthesis
that is able to generate speech audio in the voice of many different speakers,
including those unseen during training. Our system consists of three
independently trained components: (1) a speaker encoder network, trained on a
speaker verificat... | 2018-06-12T14:29:22Z | NeurIPS 2018 | Advances in Neural Information Processing Systems 31 (2018),
4485-4495 | null | null | null | null | null | null | null | null |
1,806.0491 | Bilevel Programming for Hyperparameter Optimization and Meta-Learning | ['Luca Franceschi', 'Paolo Frasconi', 'Saverio Salzo', 'Riccardo Grazzi', 'Massimilano Pontil'] | ['stat.ML', 'cs.LG'] | We introduce a framework based on bilevel programming that unifies
gradient-based hyperparameter optimization and meta-learning. We show that an
approximate version of the bilevel problem can be solved by taking into
explicit account the optimization dynamics for the inner objective. Depending
on the specific setting, ... | 2018-06-13T09:21:42Z | ICML 2018; code for replicating experiments at
https://github.com/prolearner/hyper-representation, main package (Far-HO) at
https://github.com/lucfra/FAR-HO | null | null | null | null | null | null | null | null | null |
1,806.05258 | SMHD: A Large-Scale Resource for Exploring Online Language Usage for
Multiple Mental Health Conditions | ['Arman Cohan', 'Bart Desmet', 'Andrew Yates', 'Luca Soldaini', 'Sean MacAvaney', 'Nazli Goharian'] | ['cs.CL'] | Mental health is a significant and growing public health concern. As language
usage can be leveraged to obtain crucial insights into mental health
conditions, there is a need for large-scale, labeled, mental health-related
datasets of users who have been diagnosed with one or more of such conditions.
In this paper, we ... | 2018-06-13T20:29:25Z | COLING 2018 | null | null | SMHD: a Large-Scale Resource for Exploring Online Language Usage for Multiple Mental Health Conditions | ['Arman Cohan', 'Bart Desmet', 'Andrew Yates', 'Luca Soldaini', 'Sean MacAvaney', 'Nazli Goharian'] | 2,018 | International Conference on Computational Linguistics | 141 | 48 | ['Computer Science'] |
1,806.06923 | Implicit Quantile Networks for Distributional Reinforcement Learning | ['Will Dabney', 'Georg Ostrovski', 'David Silver', 'Rémi Munos'] | ['cs.LG', 'cs.AI', 'stat.ML'] | In this work, we build on recent advances in distributional reinforcement
learning to give a generally applicable, flexible, and state-of-the-art
distributional variant of DQN. We achieve this by using quantile regression to
approximate the full quantile function for the state-action return
distribution. By reparameter... | 2018-06-14T14:28:37Z | ICML 2018 | null | null | null | null | null | null | null | null | null |
1,806.09055 | DARTS: Differentiable Architecture Search | ['Hanxiao Liu', 'Karen Simonyan', 'Yiming Yang'] | ['cs.LG', 'cs.CL', 'cs.CV', 'stat.ML'] | This paper addresses the scalability challenge of architecture search by
formulating the task in a differentiable manner. Unlike conventional approaches
of applying evolution or reinforcement learning over a discrete and
non-differentiable search space, our method is based on the continuous
relaxation of the architectu... | 2018-06-24T00:06:13Z | Published at ICLR 2019; Code and pretrained models available at
https://github.com/quark0/darts | null | null | null | null | null | null | null | null | null |
1,807.02758 | Image Super-Resolution Using Very Deep Residual Channel Attention
Networks | ['Yulun Zhang', 'Kunpeng Li', 'Kai Li', 'Lichen Wang', 'Bineng Zhong', 'Yun Fu'] | ['cs.CV'] | Convolutional neural network (CNN) depth is of crucial importance for image
super-resolution (SR). However, we observe that deeper networks for image SR
are more difficult to train. The low-resolution inputs and features contain
abundant low-frequency information, which is treated equally across channels,
hence hinderi... | 2018-07-08T05:45:45Z | To appear in ECCV 2018 | null | null | null | null | null | null | null | null | null |
1,807.04686 | Toward Convolutional Blind Denoising of Real Photographs | ['Shi Guo', 'Zifei Yan', 'Kai Zhang', 'Wangmeng Zuo', 'Lei Zhang'] | ['cs.CV'] | While deep convolutional neural networks (CNNs) have achieved impressive
success in image denoising with additive white Gaussian noise (AWGN), their
performance remains limited on real-world noisy photographs. The main reason is
that their learned models are easy to overfit on the simplified AWGN model
which deviates s... | 2018-07-12T15:52:17Z | null | IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
2019 | null | null | null | null | null | null | null | null |
1,807.10165 | UNet++: A Nested U-Net Architecture for Medical Image Segmentation | ['Zongwei Zhou', 'Md Mahfuzur Rahman Siddiquee', 'Nima Tajbakhsh', 'Jianming Liang'] | ['cs.CV', 'cs.LG', 'eess.IV', 'stat.ML'] | In this paper, we present UNet++, a new, more powerful architecture for
medical image segmentation. Our architecture is essentially a deeply-supervised
encoder-decoder network where the encoder and decoder sub-networks are
connected through a series of nested, dense skip pathways. The re-designed skip
pathways aim at r... | 2018-07-18T04:08:21Z | 8 pages, 3 figures, 3 tables, accepted by 4th Deep Learning in
Medical Image Analysis (DLMIA) Workshop | null | null | UNet++: A Nested U-Net Architecture for Medical Image Segmentation | ['Zongwei Zhou', 'M. R. Siddiquee', 'Nima Tajbakhsh', 'Jianming Liang'] | 2,018 | DLMIA/ML-CDS@MICCAI | 6,236 | 14 | ['Computer Science', 'Engineering', 'Mathematics', 'Medicine'] |
1,807.10221 | Unified Perceptual Parsing for Scene Understanding | ['Tete Xiao', 'Yingcheng Liu', 'Bolei Zhou', 'Yuning Jiang', 'Jian Sun'] | ['cs.CV'] | Humans recognize the visual world at multiple levels: we effortlessly
categorize scenes and detect objects inside, while also identifying the
textures and surfaces of the objects along with their different compositional
parts. In this paper, we study a new task called Unified Perceptual Parsing,
which requires the mach... | 2018-07-26T16:13:49Z | Accepted to European Conference on Computer Vision (ECCV) 2018 | null | null | Unified Perceptual Parsing for Scene Understanding | ['Tete Xiao', 'Yingcheng Liu', 'Bolei Zhou', 'Yuning Jiang', 'Jian Sun'] | 2,018 | European Conference on Computer Vision | 1,910 | 46 | ['Computer Science'] |
1,807.11164 | ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture
Design | ['Ningning Ma', 'Xiangyu Zhang', 'Hai-Tao Zheng', 'Jian Sun'] | ['cs.CV'] | Currently, the neural network architecture design is mostly guided by the
\emph{indirect} metric of computation complexity, i.e., FLOPs. However, the
\emph{direct} metric, e.g., speed, also depends on the other factors such as
memory access cost and platform characterics. Thus, this work proposes to
evaluate the direct... | 2018-07-30T04:18:25Z | null | null | null | null | null | null | null | null | null | null |
1,807.11626 | MnasNet: Platform-Aware Neural Architecture Search for Mobile | ['Mingxing Tan', 'Bo Chen', 'Ruoming Pang', 'Vijay Vasudevan', 'Mark Sandler', 'Andrew Howard', 'Quoc V. Le'] | ['cs.CV', 'cs.LG'] | Designing convolutional neural networks (CNN) for mobile devices is
challenging because mobile models need to be small and fast, yet still
accurate. Although significant efforts have been dedicated to design and
improve mobile CNNs on all dimensions, it is very difficult to manually balance
these trade-offs when there ... | 2018-07-31T01:34:21Z | Published in CVPR 2019 | CVPR 2019 | null | null | null | null | null | null | null | null |
1,808.00158 | Speaker Recognition from Raw Waveform with SincNet | ['Mirco Ravanelli', 'Yoshua Bengio'] | ['eess.AS', 'cs.LG', 'cs.SD', 'eess.SP'] | Deep learning is progressively gaining popularity as a viable alternative to
i-vectors for speaker recognition. Promising results have been recently
obtained with Convolutional Neural Networks (CNNs) when fed by raw speech
samples directly. Rather than employing standard hand-crafted features, the
latter CNNs learn low... | 2018-07-29T16:27:19Z | In Proceedings of SLT 2018 | null | null | null | null | null | null | null | null | null |
1,808.00897 | BiSeNet: Bilateral Segmentation Network for Real-time Semantic
Segmentation | ['Changqian Yu', 'Jingbo Wang', 'Chao Peng', 'Changxin Gao', 'Gang Yu', 'Nong Sang'] | ['cs.CV'] | Semantic segmentation requires both rich spatial information and sizeable
receptive field. However, modern approaches usually compromise spatial
resolution to achieve real-time inference speed, which leads to poor
performance. In this paper, we address this dilemma with a novel Bilateral
Segmentation Network (BiSeNet).... | 2018-08-02T16:34:01Z | Accepted to ECCV 2018. 17 pages, 4 figures, 9 tables | null | null | BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation | ['Changqian Yu', 'Jingbo Wang', 'Chao Peng', 'Changxin Gao', 'Gang Yu', 'N. Sang'] | 2,018 | European Conference on Computer Vision | 2,216 | 40 | ['Computer Science'] |
1,808.0357 | Densely Connected Convolutional Networks for Speech Recognition | ['Chia Yu Li', 'Ngoc Thang Vu'] | ['cs.CL'] | This paper presents our latest investigation on Densely Connected
Convolutional Networks (DenseNets) for acoustic modelling (AM) in automatic
speech recognition. DenseN-ets are very deep, compact convolutional neural
networks, which have demonstrated incredible improvements over the
state-of-the-art results on several ... | 2018-08-10T14:54:10Z | 5 pages, 3 figures, the 13th ITG conference on Speech Communication | null | null | null | null | null | null | null | null | null |
1,808.06226 | SentencePiece: A simple and language independent subword tokenizer and
detokenizer for Neural Text Processing | ['Taku Kudo', 'John Richardson'] | ['cs.CL'] | This paper describes SentencePiece, a language-independent subword tokenizer
and detokenizer designed for Neural-based text processing, including Neural
Machine Translation. It provides open-source C++ and Python implementations for
subword units. While existing subword segmentation tools assume that the input
is pre-t... | 2018-08-19T16:49:06Z | Accepted as a demo paper at EMNLP2018 | null | null | SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing | ['Taku Kudo', 'John Richardson'] | 2,018 | Conference on Empirical Methods in Natural Language Processing | 3,539 | 16 | ['Computer Science'] |
1,808.07036 | QuAC : Question Answering in Context | ['Eunsol Choi', 'He He', 'Mohit Iyyer', 'Mark Yatskar', 'Wen-tau Yih', 'Yejin Choi', 'Percy Liang', 'Luke Zettlemoyer'] | ['cs.CL', 'cs.AI', 'cs.LG'] | We present QuAC, a dataset for Question Answering in Context that contains
14K information-seeking QA dialogs (100K questions in total). The dialogs
involve two crowd workers: (1) a student who poses a sequence of freeform
questions to learn as much as possible about a hidden Wikipedia text, and (2) a
teacher who answe... | 2018-08-21T17:46:12Z | EMNLP Camera Ready | null | null | QuAC: Question Answering in Context | ['Eunsol Choi', 'He He', 'Mohit Iyyer', 'Mark Yatskar', 'Wen-tau Yih', 'Yejin Choi', 'Percy Liang', 'Luke Zettlemoyer'] | 2,018 | Conference on Empirical Methods in Natural Language Processing | 828 | 31 | ['Computer Science'] |
1,808.08127 | Recalibrating Fully Convolutional Networks with Spatial and Channel
'Squeeze & Excitation' Blocks | ['Abhijit Guha Roy', 'Nassir Navab', 'Christian Wachinger'] | ['cs.CV'] | In a wide range of semantic segmentation tasks, fully convolutional neural
networks (F-CNNs) have been successfully leveraged to achieve state-of-the-art
performance. Architectural innovations of F-CNNs have mainly been on improving
spatial encoding or network connectivity to aid gradient flow. In this article,
we aim ... | 2018-08-23T13:45:03Z | Accepted for publication in IEEE Transactions on Medical Imaging.
arXiv admin note: text overlap with arXiv:1803.02579 | null | null | Recalibrating Fully Convolutional Networks With Spatial and Channel “Squeeze and Excitation” Blocks | ['Abhijit Guha Roy', 'Nassir Navab', 'C. Wachinger'] | 2,018 | IEEE Transactions on Medical Imaging | 383 | 24 | ['Computer Science', 'Medicine'] |
1,808.08745 | Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional
Neural Networks for Extreme Summarization | ['Shashi Narayan', 'Shay B. Cohen', 'Mirella Lapata'] | ['cs.CL'] | We introduce extreme summarization, a new single-document summarization task
which does not favor extractive strategies and calls for an abstractive
modeling approach. The idea is to create a short, one-sentence news summary
answering the question "What is the article about?". We collect a real-world,
large-scale datas... | 2018-08-27T09:08:18Z | 11, 2018 Conference on Empirical Methods in Natural Language
Processing, EMNLP 2018 | null | null | Don’t Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization | ['Shashi Narayan', 'Shay B. Cohen', 'Mirella Lapata'] | 2,018 | Conference on Empirical Methods in Natural Language Processing | 1,689 | 42 | ['Computer Science'] |
1,808.09121 | WiC: the Word-in-Context Dataset for Evaluating Context-Sensitive
Meaning Representations | ['Mohammad Taher Pilehvar', 'Jose Camacho-Collados'] | ['cs.CL'] | By design, word embeddings are unable to model the dynamic nature of words'
semantics, i.e., the property of words to correspond to potentially different
meanings. To address this limitation, dozens of specialized meaning
representation techniques such as sense or contextualized embeddings have been
proposed. However, ... | 2018-08-28T05:16:35Z | NAACL 2019 | null | null | WiC: the Word-in-Context Dataset for Evaluating Context-Sensitive Meaning Representations | ['Mohammad Taher Pilehvar', 'José Camacho-Collados'] | 2,018 | North American Chapter of the Association for Computational Linguistics | 493 | 29 | ['Computer Science'] |
1,808.10583 | AISHELL-2: Transforming Mandarin ASR Research Into Industrial Scale | ['Jiayu Du', 'Xingyu Na', 'Xuechen Liu', 'Hui Bu'] | ['cs.CL'] | AISHELL-1 is by far the largest open-source speech corpus available for
Mandarin speech recognition research. It was released with a baseline system
containing solid training and testing pipelines for Mandarin ASR. In AISHELL-2,
1000 hours of clean read-speech data from iOS is published, which is free for
academic usag... | 2018-08-31T03:11:08Z | null | null | null | AISHELL-2: Transforming Mandarin ASR Research Into Industrial Scale | ['Jiayu Du', 'Xingyu Na', 'Xuechen Liu', 'Hui Bu'] | 2,018 | arXiv.org | 287 | 15 | ['Computer Science'] |
1,808.10584 | Learning to Describe Differences Between Pairs of Similar Images | ['Harsh Jhamtani', 'Taylor Berg-Kirkpatrick'] | ['cs.CL', 'cs.CV'] | In this paper, we introduce the task of automatically generating text to
describe the differences between two similar images. We collect a new dataset
by crowd-sourcing difference descriptions for pairs of image frames extracted
from video-surveillance footage. Annotators were asked to succinctly describe
all the diffe... | 2018-08-31T03:15:28Z | EMNLP 2018 | null | null | null | null | null | null | null | null | null |
1,809.00219 | ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks | ['Xintao Wang', 'Ke Yu', 'Shixiang Wu', 'Jinjin Gu', 'Yihao Liu', 'Chao Dong', 'Chen Change Loy', 'Yu Qiao', 'Xiaoou Tang'] | ['cs.CV'] | The Super-Resolution Generative Adversarial Network (SRGAN) is a seminal work
that is capable of generating realistic textures during single image
super-resolution. However, the hallucinated details are often accompanied with
unpleasant artifacts. To further enhance the visual quality, we thoroughly
study three key com... | 2018-09-01T16:21:03Z | To appear in ECCV 2018 workshop. Won Region 3 in the PIRM2018-SR
Challenge. Code and models are at https://github.com/xinntao/ESRGAN | null | null | null | null | null | null | null | null | null |
1,809.02627 | Unity: A General Platform for Intelligent Agents | ['Arthur Juliani', 'Vincent-Pierre Berges', 'Ervin Teng', 'Andrew Cohen', 'Jonathan Harper', 'Chris Elion', 'Chris Goy', 'Yuan Gao', 'Hunter Henry', 'Marwan Mattar', 'Danny Lange'] | ['cs.LG', 'cs.AI', 'cs.NE', 'stat.ML'] | Recent advances in artificial intelligence have been driven by the presence
of increasingly realistic and complex simulated environments. However, many of
the existing environments provide either unrealistic visuals, inaccurate
physics, low task complexity, restricted agent perspective, or a limited
capacity for intera... | 2018-09-07T18:13:25Z | null | null | null | null | null | null | null | null | null | null |
1,809.02789 | Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book
Question Answering | ['Todor Mihaylov', 'Peter Clark', 'Tushar Khot', 'Ashish Sabharwal'] | ['cs.CL'] | We present a new kind of question answering dataset, OpenBookQA, modeled
after open book exams for assessing human understanding of a subject. The open
book that comes with our questions is a set of 1329 elementary level science
facts. Roughly 6000 questions probe an understanding of these facts and their
application t... | 2018-09-08T11:47:16Z | Published as conference long paper at EMNLP 2018 | null | null | Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering | ['Todor Mihaylov', 'Peter Clark', 'Tushar Khot', 'Ashish Sabharwal'] | 2,018 | Conference on Empirical Methods in Natural Language Processing | 1,574 | 53 | ['Computer Science'] |
1,809.02922 | Transforming Question Answering Datasets Into Natural Language Inference
Datasets | ['Dorottya Demszky', 'Kelvin Guu', 'Percy Liang'] | ['cs.CL'] | Existing datasets for natural language inference (NLI) have propelled
research on language understanding. We propose a new method for automatically
deriving NLI datasets from the growing abundance of large-scale question
answering datasets. Our approach hinges on learning a sentence transformation
model which converts ... | 2018-09-09T05:03:34Z | 11 pages, 6 figures | null | null | null | null | null | null | null | null | null |
1,809.03207 | Beyond the Selected Completely At Random Assumption for Learning from
Positive and Unlabeled Data | ['Jessa Bekker', 'Pieter Robberechts', 'Jesse Davis'] | ['cs.LG', 'stat.ML'] | Most positive and unlabeled data is subject to selection biases. The labeled
examples can, for example, be selected from the positive set because they are
easier to obtain or more obviously positive. This paper investigates how
learning can be ena BHbled in this setting. We propose and theoretically
analyze an empirica... | 2018-09-10T09:23:32Z | null | European Conference on Machine Learning and Principles and
Practice of Knowledge Discovery in Databases 2019 (ECMLPKDD 2019) | null | null | null | null | null | null | null | null |
1,809.04281 | Music Transformer | ['Cheng-Zhi Anna Huang', 'Ashish Vaswani', 'Jakob Uszkoreit', 'Noam Shazeer', 'Ian Simon', 'Curtis Hawthorne', 'Andrew M. Dai', 'Matthew D. Hoffman', 'Monica Dinculescu', 'Douglas Eck'] | ['cs.LG', 'cs.SD', 'eess.AS', 'stat.ML'] | Music relies heavily on repetition to build structure and meaning.
Self-reference occurs on multiple timescales, from motifs to phrases to reusing
of entire sections of music, such as in pieces with ABA structure. The
Transformer (Vaswani et al., 2017), a sequence model based on self-attention,
has achieved compelling ... | 2018-09-12T07:15:26Z | Improved skewing section and accompanying figures. Previous titles
are "An Improved Relative Self-Attention Mechanism for Transformer with
Application to Music Generation" and "Music Transformer" | null | null | null | null | null | null | null | null | null |
1,809.05053 | XNLI: Evaluating Cross-lingual Sentence Representations | ['Alexis Conneau', 'Guillaume Lample', 'Ruty Rinott', 'Adina Williams', 'Samuel R. Bowman', 'Holger Schwenk', 'Veselin Stoyanov'] | ['cs.CL', 'cs.AI', 'cs.LG'] | State-of-the-art natural language processing systems rely on supervision in
the form of annotated data to learn competent models. These models are
generally trained on data in a single language (usually English), and cannot be
directly used beyond that language. Since collecting data in every language is
not realistic,... | 2018-09-13T16:39:53Z | EMNLP 2018 | null | null | null | null | null | null | null | null | null |
1,809.05972 | Generating Informative and Diverse Conversational Responses via
Adversarial Information Maximization | ['Yizhe Zhang', 'Michel Galley', 'Jianfeng Gao', 'Zhe Gan', 'Xiujun Li', 'Chris Brockett', 'Bill Dolan'] | ['cs.CL', 'cs.AI'] | Responses generated by neural conversational models tend to lack
informativeness and diversity. We present Adversarial Information Maximization
(AIM), an adversarial learning strategy that addresses these two related but
distinct problems. To foster response diversity, we leverage adversarial
training that allows distr... | 2018-09-16T22:45:51Z | NIPS 2018 | null | null | null | null | null | null | null | null | null |
1,809.08887 | Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain
Semantic Parsing and Text-to-SQL Task | ['Tao Yu', 'Rui Zhang', 'Kai Yang', 'Michihiro Yasunaga', 'Dongxu Wang', 'Zifan Li', 'James Ma', 'Irene Li', 'Qingning Yao', 'Shanelle Roman', 'Zilin Zhang', 'Dragomir Radev'] | ['cs.CL', 'cs.AI'] | We present Spider, a large-scale, complex and cross-domain semantic parsing
and text-to-SQL dataset annotated by 11 college students. It consists of 10,181
questions and 5,693 unique complex SQL queries on 200 databases with multiple
tables, covering 138 different domains. We define a new complex and
cross-domain seman... | 2018-09-24T13:03:13Z | EMNLP 2018, Long Paper | null | null | Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task | ['Tao Yu', 'Rui Zhang', 'Kai-Chou Yang', 'Michihiro Yasunaga', 'Dongxu Wang', 'Zifan Li', 'James Ma', 'Irene Z Li', 'Qingning Yao', 'Shanelle Roman', 'Zilin Zhang', 'Dragomir R. Radev'] | 2,018 | Conference on Empirical Methods in Natural Language Processing | 1,250 | 45 | ['Computer Science'] |
1,809.08895 | Neural Speech Synthesis with Transformer Network | ['Naihan Li', 'Shujie Liu', 'Yanqing Liu', 'Sheng Zhao', 'Ming Liu', 'Ming Zhou'] | ['cs.CL'] | Although end-to-end neural text-to-speech (TTS) methods (such as Tacotron2)
are proposed and achieve state-of-the-art performance, they still suffer from
two problems: 1) low efficiency during training and inference; 2) hard to model
long dependency using current recurrent neural networks (RNNs). Inspired by the
succes... | 2018-09-19T07:41:17Z | null | null | null | null | null | null | null | null | null | null |
1,809.096 | HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question
Answering | ['Zhilin Yang', 'Peng Qi', 'Saizheng Zhang', 'Yoshua Bengio', 'William W. Cohen', 'Ruslan Salakhutdinov', 'Christopher D. Manning'] | ['cs.CL'] | Existing question answering (QA) datasets fail to train QA systems to perform
complex reasoning and provide explanations for answers. We introduce HotpotQA,
a new dataset with 113k Wikipedia-based question-answer pairs with four key
features: (1) the questions require finding and reasoning over multiple
supporting docu... | 2018-09-25T17:28:20Z | EMNLP 2018 long paper. The first three authors contribute equally.
Data, code, and blog posts available at https://hotpotqa.github.io/ | null | null | null | null | null | null | null | null | null |
1,810.03993 | Model Cards for Model Reporting | ['Margaret Mitchell', 'Simone Wu', 'Andrew Zaldivar', 'Parker Barnes', 'Lucy Vasserman', 'Ben Hutchinson', 'Elena Spitzer', 'Inioluwa Deborah Raji', 'Timnit Gebru'] | ['cs.LG', 'cs.AI'] | Trained machine learning models are increasingly used to perform high-impact
tasks in areas such as law enforcement, medicine, education, and employment. In
order to clarify the intended use cases of machine learning models and minimize
their usage in contexts for which they are not well suited, we recommend that
relea... | 2018-10-05T22:33:43Z | null | FAT* '19: Conference on Fairness, Accountability, and
Transparency, January 29--31, 2019, Atlanta, GA, USA | 10.1145/3287560.3287596 | Model Cards for Model Reporting | ['Margaret Mitchell', 'Simone Wu', 'Andrew Zaldivar', 'Parker Barnes', 'Lucy Vasserman', 'Ben Hutchinson', 'Elena Spitzer', 'Inioluwa Deborah Raji', 'Timnit Gebru'] | 2,018 | FAT | 1,924 | 48 | ['Computer Science'] |
1,810.0402 | A Comprehensive Survey of Deep Learning for Image Captioning | ['Md. Zakir Hossain', 'Ferdous Sohel', 'Mohd Fairuz Shiratuddin', 'Hamid Laga'] | ['cs.CV', 'cs.LG', 'stat.ML'] | Generating a description of an image is called image captioning. Image
captioning requires to recognize the important objects, their attributes and
their relationships in an image. It also needs to generate syntactically and
semantically correct sentences. Deep learning-based techniques are capable of
handling the comp... | 2018-10-06T16:31:52Z | 36 Pages, Accepted as a Journal Paper in ACM Computing Surveys
(October 2018) | null | null | A Comprehensive Survey of Deep Learning for Image Captioning | ['Md. Zakir Hossain', 'Ferdous Sohel', 'M. Shiratuddin', 'Hamid Laga'] | 2,018 | ACM Computing Surveys | 781 | 176 | ['Computer Science', 'Mathematics'] |
1,810.04805 | BERT: Pre-training of Deep Bidirectional Transformers for Language
Understanding | ['Jacob Devlin', 'Ming-Wei Chang', 'Kenton Lee', 'Kristina Toutanova'] | ['cs.CL'] | We introduce a new language representation model called BERT, which stands
for Bidirectional Encoder Representations from Transformers. Unlike recent
language representation models, BERT is designed to pre-train deep
bidirectional representations from unlabeled text by jointly conditioning on
both left and right contex... | 2018-10-11T00:50:01Z | null | null | null | null | null | null | null | null | null | null |
1,810.05424 | Real-time self-adaptive deep stereo | ['Alessio Tonioni', 'Fabio Tosi', 'Matteo Poggi', 'Stefano Mattoccia', 'Luigi Di Stefano'] | ['cs.CV'] | Deep convolutional neural networks trained end-to-end are the
state-of-the-art methods to regress dense disparity maps from stereo pairs.
These models, however, suffer from a notable decrease in accuracy when exposed
to scenarios significantly different from the training set, e.g., real vs
synthetic images, etc.). We a... | 2018-10-12T09:17:53Z | Accepted at CVPR2019 as oral presentation. Code Available
https://github.com/CVLAB-Unibo/Real-time-self-adaptive-deep-stereo | null | null | null | null | null | null | null | null | null |
1,810.06694 | Word Embeddings from Large-Scale Greek Web Content | ['Stamatis Outsios', 'Konstantinos Skianis', 'Polykarpos Meladianos', 'Christos Xypolopoulos', 'Michalis Vazirgiannis'] | ['cs.CL'] | Word embeddings are undoubtedly very useful components in many NLP tasks. In
this paper, we present word embeddings and other linguistic resources trained
on the largest to date digital Greek language corpus. We also present a live
web tool for testing the Greek word embeddings, by offering "analogy",
"similarity score... | 2018-10-08T17:19:07Z | null | null | null | null | null | null | null | null | null | null |
1,810.09305 | WikiHow: A Large Scale Text Summarization Dataset | ['Mahnaz Koupaee', 'William Yang Wang'] | ['cs.CL', 'cs.IR', 'cs.LG'] | Sequence-to-sequence models have recently gained the state of the art
performance in summarization. However, not too many large-scale high-quality
datasets are available and almost all the available ones are mainly news
articles with specific writing style. Moreover, abstractive human-style systems
involving descriptio... | 2018-10-18T05:29:41Z | null | null | null | WikiHow: A Large Scale Text Summarization Dataset | ['Mahnaz Koupaee', 'William Yang Wang'] | 2,018 | arXiv.org | 295 | 18 | ['Computer Science'] |
1,810.10667 | Truncated Back-propagation for Bilevel Optimization | ['Amirreza Shaban', 'Ching-An Cheng', 'Nathan Hatch', 'Byron Boots'] | ['cs.LG', 'stat.ML'] | Bilevel optimization has been recently revisited for designing and analyzing
algorithms in hyperparameter tuning and meta learning tasks. However, due to
its nested structure, evaluating exact gradients for high-dimensional problems
is computationally challenging. One heuristic to circumvent this difficulty is
to use t... | 2018-10-25T00:49:36Z | null | The International Conference on Artificial Intelligence and
Statistics (AISTATS) 2019 | null | null | null | null | null | null | null | null |
1,810.11654 | 3D MRI brain tumor segmentation using autoencoder regularization | ['Andriy Myronenko'] | ['cs.CV', 'q-bio.NC'] | Automated segmentation of brain tumors from 3D magnetic resonance images
(MRIs) is necessary for the diagnosis, monitoring, and treatment planning of
the disease. Manual delineation practices require anatomical knowledge, are
expensive, time consuming and can be inaccurate due to human error. Here, we
describe a semant... | 2018-10-27T14:42:13Z | null | null | null | null | null | null | null | null | null | null |
1,810.12368 | A Pragmatic Guide to Geoparsing Evaluation | ['Milan Gritta', 'Mohammad Taher Pilehvar', 'Nigel Collier'] | ['cs.CL'] | Empirical methods in geoparsing have thus far lacked a standard evaluation
framework describing the task, metrics and data used to compare
state-of-the-art systems. Evaluation is further made inconsistent, even
unrepresentative of real-world usage by the lack of distinction between the
different types of toponyms, whic... | 2018-10-29T19:22:12Z | Accepted at Language Resources and Evaluation (Springer Journal) | null | null | null | null | null | null | null | null | null |
1,810.1244 | TallyQA: Answering Complex Counting Questions | ['Manoj Acharya', 'Kushal Kafle', 'Christopher Kanan'] | ['cs.CV'] | Most counting questions in visual question answering (VQA) datasets are
simple and require no more than object detection. Here, we study algorithms for
complex counting questions that involve relationships between objects,
attribute identification, reasoning, and more. To do this, we created TallyQA,
the world's larges... | 2018-10-29T22:29:45Z | To appear in AAAI 2019 ( To download the dataset please go to
http://www.manojacharya.com/ ) | null | null | null | null | null | null | null | null | null |
1,810.12715 | On the Effectiveness of Interval Bound Propagation for Training
Verifiably Robust Models | ['Sven Gowal', 'Krishnamurthy Dvijotham', 'Robert Stanforth', 'Rudy Bunel', 'Chongli Qin', 'Jonathan Uesato', 'Relja Arandjelovic', 'Timothy Mann', 'Pushmeet Kohli'] | ['cs.LG', 'cs.CR', 'stat.ML'] | Recent work has shown that it is possible to train deep neural networks that
are provably robust to norm-bounded adversarial perturbations. Most of these
methods are based on minimizing an upper bound on the worst-case loss over all
possible adversarial perturbations. While these techniques show promise, they
often res... | 2018-10-30T13:12:47Z | [v2] Best paper at NeurIPS SECML 2018 Workshop [v4] Accepted at ICCV
2019 under the title "Scalable Verified Training for Provably Robust Image
Classification" | null | null | null | null | null | null | null | null | null |
1,810.12885 | ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading
Comprehension | ['Sheng Zhang', 'Xiaodong Liu', 'Jingjing Liu', 'Jianfeng Gao', 'Kevin Duh', 'Benjamin Van Durme'] | ['cs.CL'] | We present a large-scale dataset, ReCoRD, for machine reading comprehension
requiring commonsense reasoning. Experiments on this dataset demonstrate that
the performance of state-of-the-art MRC systems fall far behind human
performance. ReCoRD represents a challenge for future research to bridge the
gap between human a... | 2018-10-30T17:32:16Z | 14 pages | null | null | null | null | null | null | null | null | null |
1,810.12894 | Exploration by Random Network Distillation | ['Yuri Burda', 'Harrison Edwards', 'Amos Storkey', 'Oleg Klimov'] | ['cs.LG', 'cs.AI', 'stat.ML'] | We introduce an exploration bonus for deep reinforcement learning methods
that is easy to implement and adds minimal overhead to the computation
performed. The bonus is the error of a neural network predicting features of
the observations given by a fixed randomly initialized neural network. We also
introduce a method ... | 2018-10-30T17:44:42Z | null | null | null | null | null | null | null | null | null | null |
1,810.13273 | Ionospheric activity prediction using convolutional recurrent neural
networks | ['Alexandre Boulch', 'Noëlie Cherrier', 'Thibaut Castaings'] | ['cs.CV', 'cs.LG'] | The ionosphere electromagnetic activity is a major factor of the quality of
satellite telecommunications, Global Navigation Satellite Systems (GNSS) and
other vital space applications. Being able to forecast globally the Total
Electron Content (TEC) would enable a better anticipation of potential
performance degradatio... | 2018-10-31T13:25:17Z | Under submission at IEEE Transactions on Big Data | null | null | Ionospheric activity prediction using convolutional recurrent neural networks | ['Alexandre Boulch', 'Noëlie Cherrier', 'T. Castaings'] | 2,018 | arXiv.org | 21 | 35 | ['Computer Science'] |
1,811.00002 | WaveGlow: A Flow-based Generative Network for Speech Synthesis | ['Ryan Prenger', 'Rafael Valle', 'Bryan Catanzaro'] | ['cs.SD', 'cs.AI', 'cs.LG', 'eess.AS', 'stat.ML'] | In this paper we propose WaveGlow: a flow-based network capable of generating
high quality speech from mel-spectrograms. WaveGlow combines insights from Glow
and WaveNet in order to provide fast, efficient and high-quality audio
synthesis, without the need for auto-regression. WaveGlow is implemented using
only a singl... | 2018-10-31T03:22:25Z | 5 pages, 1 figure, 1 table, 13 equations | null | null | null | null | null | null | null | null | null |
1,811.00671 | Dialogue Natural Language Inference | ['Sean Welleck', 'Jason Weston', 'Arthur Szlam', 'Kyunghyun Cho'] | ['cs.CL', 'cs.AI'] | Consistency is a long standing issue faced by dialogue models. In this paper,
we frame the consistency of dialogue agents as natural language inference (NLI)
and create a new natural language inference dataset called Dialogue NLI. We
propose a method which demonstrates that a model trained on Dialogue NLI can be
used t... | 2018-11-01T23:10:03Z | null | null | null | Dialogue Natural Language Inference | ['S. Welleck', 'J. Weston', 'Arthur Szlam', 'Kyunghyun Cho'] | 2,018 | Annual Meeting of the Association for Computational Linguistics | 254 | 32 | ['Computer Science'] |
1,811.00937 | CommonsenseQA: A Question Answering Challenge Targeting Commonsense
Knowledge | ['Alon Talmor', 'Jonathan Herzig', 'Nicholas Lourie', 'Jonathan Berant'] | ['cs.CL', 'cs.AI', 'cs.LG'] | When answering a question, people often draw upon their rich world knowledge
in addition to the particular context. Recent work has focused primarily on
answering questions given some relevant document or context, and required very
little general background. To investigate question answering with prior
knowledge, we pr... | 2018-11-02T15:34:29Z | accepted as a long paper at NAACL 2019 | null | null | CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge | ['Alon Talmor', 'Jonathan Herzig', 'Nicholas Lourie', 'Jonathan Berant'] | 2,019 | North American Chapter of the Association for Computational Linguistics | 1,754 | 44 | ['Computer Science'] |
1,811.01241 | Wizard of Wikipedia: Knowledge-Powered Conversational agents | ['Emily Dinan', 'Stephen Roller', 'Kurt Shuster', 'Angela Fan', 'Michael Auli', 'Jason Weston'] | ['cs.CL'] | In open-domain dialogue intelligent agents should exhibit the use of
knowledge, however there are few convincing demonstrations of this to date. The
most popular sequence to sequence models typically "generate and hope" generic
utterances that can be memorized in the weights of the model when mapping from
input utteran... | 2018-11-03T16:11:29Z | null | null | null | Wizard of Wikipedia: Knowledge-Powered Conversational agents | ['Emily Dinan', 'Stephen Roller', 'Kurt Shuster', 'Angela Fan', 'Michael Auli', 'J. Weston'] | 2,018 | International Conference on Learning Representations | 952 | 33 | ['Computer Science'] |
1,811.02508 | SDR - half-baked or well done? | ['Jonathan Le Roux', 'Scott Wisdom', 'Hakan Erdogan', 'John R. Hershey'] | ['cs.SD', 'eess.AS'] | In speech enhancement and source separation, signal-to-noise ratio is a
ubiquitous objective measure of denoising/separation quality. A decade ago, the
BSS_eval toolkit was developed to give researchers worldwide a way to evaluate
the quality of their algorithms in a simple, fair, and hopefully insightful
way: it attem... | 2018-11-06T17:20:05Z | null | null | null | SDR – Half-baked or Well Done? | ['Jonathan Le Roux', 'Scott Wisdom', 'Hakan Erdogan', 'J. Hershey'] | 2,018 | IEEE International Conference on Acoustics, Speech, and Signal Processing | 1,209 | 26 | ['Computer Science', 'Engineering'] |
1,811.08008 | End-to-End Retrieval in Continuous Space | ['Daniel Gillick', 'Alessandro Presta', 'Gaurav Singh Tomar'] | ['cs.IR', 'cs.CL', 'cs.LG'] | Most text-based information retrieval (IR) systems index objects by words or
phrases. These discrete systems have been augmented by models that use
embeddings to measure similarity in continuous space. But continuous-space
models are typically used just to re-rank the top candidates. We consider the
problem of end-to-e... | 2018-11-19T22:23:59Z | null | null | null | null | null | null | null | null | null | null |
1,811.11168 | Deformable ConvNets v2: More Deformable, Better Results | ['Xizhou Zhu', 'Han Hu', 'Stephen Lin', 'Jifeng Dai'] | ['cs.CV'] | The superior performance of Deformable Convolutional Networks arises from its
ability to adapt to the geometric variations of objects. Through an examination
of its adaptive behavior, we observe that while the spatial support for its
neural features conforms more closely than regular ConvNets to object
structure, this ... | 2018-11-27T18:58:11Z | null | null | null | Deformable ConvNets V2: More Deformable, Better Results | ['Xizhou Zhu', 'Han Hu', 'Stephen Lin', 'Jifeng Dai'] | 2,018 | Computer Vision and Pattern Recognition | 2,039 | 48 | ['Computer Science'] |
1,811.11721 | CCNet: Criss-Cross Attention for Semantic Segmentation | ['Zilong Huang', 'Xinggang Wang', 'Yunchao Wei', 'Lichao Huang', 'Humphrey Shi', 'Wenyu Liu', 'Thomas S. Huang'] | ['cs.CV'] | Contextual information is vital in visual understanding problems, such as
semantic segmentation and object detection. We propose a Criss-Cross Network
(CCNet) for obtaining full-image contextual information in a very effective and
efficient way. Concretely, for each pixel, a novel criss-cross attention module
harvests ... | 2018-11-28T18:18:27Z | IEEE TPAMI 2020 & ICCV 2019 | null | null | null | null | null | null | null | null | null |
1,811.12231 | ImageNet-trained CNNs are biased towards texture; increasing shape bias
improves accuracy and robustness | ['Robert Geirhos', 'Patricia Rubisch', 'Claudio Michaelis', 'Matthias Bethge', 'Felix A. Wichmann', 'Wieland Brendel'] | ['cs.CV', 'cs.AI', 'cs.LG', 'q-bio.NC', 'stat.ML'] | Convolutional Neural Networks (CNNs) are commonly thought to recognise
objects by learning increasingly complex representations of object shapes. Some
recent studies suggest a more important role of image textures. We here put
these conflicting hypotheses to a quantitative test by evaluating CNNs and
human observers on... | 2018-11-29T15:04:05Z | Accepted at ICLR 2019 (oral) | null | null | null | null | null | null | null | null | null |
1,811.12506 | 3D Semi-Supervised Learning with Uncertainty-Aware Multi-View
Co-Training | ['Yingda Xia', 'Fengze Liu', 'Dong Yang', 'Jinzheng Cai', 'Lequan Yu', 'Zhuotun Zhu', 'Daguang Xu', 'Alan Yuille', 'Holger Roth'] | ['cs.CV'] | While making a tremendous impact in various fields, deep neural networks
usually require large amounts of labeled data for training which are expensive
to collect in many applications, especially in the medical domain. Unlabeled
data, on the other hand, is much more abundant. Semi-supervised learning
techniques, such a... | 2018-11-29T21:58:53Z | Accepted to WACV 2020 | null | null | null | null | null | null | null | null | null |
1,811.12596 | Parsing R-CNN for Instance-Level Human Analysis | ['Lu Yang', 'Qing Song', 'Zhihui Wang', 'Ming Jiang'] | ['cs.CV'] | Instance-level human analysis is common in real-life scenarios and has
multiple manifestations, such as human part segmentation, dense pose
estimation, human-object interactions, etc. Models need to distinguish
different human instances in the image panel and learn rich features to
represent the details of each instanc... | 2018-11-30T03:21:11Z | COCO 2018 DensePose Challenge Winner | null | null | null | null | null | null | null | null | null |
1,812.00076 | Scalable Graph Learning for Anti-Money Laundering: A First Look | ['Mark Weber', 'Jie Chen', 'Toyotaro Suzumura', 'Aldo Pareja', 'Tengfei Ma', 'Hiroki Kanezashi', 'Tim Kaler', 'Charles E. Leiserson', 'Tao B. Schardl'] | ['cs.SI', 'cs.AI', 'cs.LG'] | Organized crime inflicts human suffering on a genocidal scale: the Mexican
drug cartels have murdered 150,000 people since 2006, upwards of 700,000 people
per year are "exported" in a human trafficking industry enslaving an estimated
40 million people. These nefarious industries rely on sophisticated money
laundering s... | 2018-11-30T22:18:45Z | NeurIPS 2018 Workshop on Challenges and Opportunities for AI in
Financial Services: the Impact of Fairness, Explainability, Accuracy, and
Privacy, Montreal, Canada | null | null | null | null | null | null | null | null | null |
1,812.01187 | Bag of Tricks for Image Classification with Convolutional Neural
Networks | ['Tong He', 'Zhi Zhang', 'Hang Zhang', 'Zhongyue Zhang', 'Junyuan Xie', 'Mu Li'] | ['cs.CV'] | Much of the recent progress made in image classification research can be
credited to training procedure refinements, such as changes in data
augmentations and optimization methods. In the literature, however, most
refinements are either briefly mentioned as implementation details or only
visible in source code. In this... | 2018-12-04T03:07:35Z | 10 pages, 9 tables, 4 figures | null | null | null | null | null | null | null | null | null |
1,812.01243 | Efficient Attention: Attention with Linear Complexities | ['Zhuoran Shen', 'Mingyuan Zhang', 'Haiyu Zhao', 'Shuai Yi', 'Hongsheng Li'] | ['cs.CV', 'cs.AI', 'cs.LG', 'I.2.6; I.2.10; I.4.8; I.4.6'] | Dot-product attention has wide applications in computer vision and natural
language processing. However, its memory and computational costs grow
quadratically with the input size. Such growth prohibits its application on
high-resolution inputs. To remedy this drawback, this paper proposes a novel
efficient attention me... | 2018-12-04T06:41:46Z | To appear at WACV 2021 | null | null | null | null | null | null | null | null | null |
1,812.01717 | Towards Accurate Generative Models of Video: A New Metric & Challenges | ['Thomas Unterthiner', 'Sjoerd van Steenkiste', 'Karol Kurach', 'Raphael Marinier', 'Marcin Michalski', 'Sylvain Gelly'] | ['cs.CV', 'cs.AI', 'cs.LG', 'cs.NE', 'stat.ML'] | Recent advances in deep generative models have lead to remarkable progress in
synthesizing high quality images. Following their successful application in
image processing and representation learning, an important next step is to
consider videos. Learning generative models of video is a much harder task,
requiring a mod... | 2018-12-03T03:57:42Z | null | null | null | Towards Accurate Generative Models of Video: A New Metric & Challenges | ['Thomas Unterthiner', 'Sjoerd van Steenkiste', 'Karol Kurach', 'Raphaël Marinier', 'Marcin Michalski', 'S. Gelly'] | 2,018 | arXiv.org | 749 | 53 | ['Computer Science', 'Mathematics'] |
1,812.01754 | Moment Matching for Multi-Source Domain Adaptation | ['Xingchao Peng', 'Qinxun Bai', 'Xide Xia', 'Zijun Huang', 'Kate Saenko', 'Bo Wang'] | ['cs.CV'] | Conventional unsupervised domain adaptation (UDA) assumes that training data
are sampled from a single domain. This neglects the more practical scenario
where training data are collected from multiple sources, requiring multi-source
domain adaptation. We make three major contributions towards addressing this
problem. F... | 2018-12-04T23:43:37Z | Accepted As Oral Paper in the IEEE International Conference on
Computer Vision 2019 | null | null | null | null | null | null | null | null | null |
1,812.03443 | FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural
Architecture Search | ['Bichen Wu', 'Xiaoliang Dai', 'Peizhao Zhang', 'Yanghan Wang', 'Fei Sun', 'Yiming Wu', 'Yuandong Tian', 'Peter Vajda', 'Yangqing Jia', 'Kurt Keutzer'] | ['cs.CV'] | Designing accurate and efficient ConvNets for mobile devices is challenging
because the design space is combinatorially large. Due to this, previous neural
architecture search (NAS) methods are computationally expensive. ConvNet
architecture optimality depends on factors such as input resolution and target
devices. How... | 2018-12-09T08:24:50Z | null | null | null | null | null | null | null | null | null | null |
1,812.06164 | Inverse Cooking: Recipe Generation from Food Images | ['Amaia Salvador', 'Michal Drozdzal', 'Xavier Giro-i-Nieto', 'Adriana Romero'] | ['cs.CV'] | People enjoy food photography because they appreciate food. Behind each meal
there is a story described in a complex recipe and, unfortunately, by simply
looking at a food image we do not have access to its preparation process.
Therefore, in this paper we introduce an inverse cooking system that recreates
cooking recip... | 2018-12-14T20:59:33Z | CVPR 2019 | null | null | Inverse Cooking: Recipe Generation From Food Images | ['Amaia Salvador', 'M. Drozdzal', 'Xavier Giró-i-Nieto', 'Adriana Romero'] | 2,018 | Computer Vision and Pattern Recognition | 148 | 65 | ['Computer Science'] |
1,812.08008 | OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity
Fields | ['Zhe Cao', 'Gines Hidalgo', 'Tomas Simon', 'Shih-En Wei', 'Yaser Sheikh'] | ['cs.CV'] | Realtime multi-person 2D pose estimation is a key component in enabling
machines to have an understanding of people in images and videos. In this work,
we present a realtime approach to detect the 2D pose of multiple people in an
image. The proposed method uses a nonparametric representation, which we refer
to as Part ... | 2018-12-18T18:50:33Z | Journal version of arXiv:1611.08050, with better accuracy and faster
speed, release a new foot keypoint dataset:
https://cmu-perceptual-computing-lab.github.io/foot_keypoint_dataset/ | null | null | null | null | null | null | null | null | null |
1,812.08092 | A standardized Project Gutenberg corpus for statistical analysis of
natural language and quantitative linguistics | ['Martin Gerlach', 'Francesc Font-Clos'] | ['cs.CL', 'cs.DL', 'cs.IR', 'physics.soc-ph'] | The use of Project Gutenberg (PG) as a text corpus has been extremely popular
in statistical analysis of language for more than 25 years. However, in
contrast to other major linguistic datasets of similar importance, no
consensual full version of PG exists to date. In fact, most PG studies so far
either consider only a... | 2018-12-19T17:10:14Z | null | null | null | A Standardized Project Gutenberg Corpus for Statistical Analysis of Natural Language and Quantitative Linguistics | ['Martin Gerlach', 'Francesc Font-Clos'] | 2,018 | Entropy | 97 | 67 | ['Computer Science', 'Medicine', 'Physics'] |
1,812.08693 | An Empirical Study on Learning Bug-Fixing Patches in the Wild via Neural
Machine Translation | ['Michele Tufano', 'Cody Watson', 'Gabriele Bavota', 'Massimiliano Di Penta', 'Martin White', 'Denys Poshyvanyk'] | ['cs.SE'] | Millions of open-source projects with numerous bug fixes are available in
code repositories. This proliferation of software development histories can be
leveraged to learn how to fix common programming bugs. To explore such a
potential, we perform an empirical study to assess the feasibility of using
Neural Machine Tra... | 2018-12-20T16:52:30Z | Accepted to the ACM Transactions on Software Engineering and
Methodology | null | null | An Empirical Study on Learning Bug-Fixing Patches in the Wild via Neural Machine Translation | ['Michele Tufano', 'Cody Watson', 'G. Bavota', 'M. D. Penta', 'Martin White', 'D. Poshyvanyk'] | 2,018 | ACM Transactions on Software Engineering and Methodology | 368 | 98 | ['Computer Science'] |
1,812.10464 | Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual
Transfer and Beyond | ['Mikel Artetxe', 'Holger Schwenk'] | ['cs.CL', 'cs.AI', 'cs.LG'] | We introduce an architecture to learn joint multilingual sentence
representations for 93 languages, belonging to more than 30 different families
and written in 28 different scripts. Our system uses a single BiLSTM encoder
with a shared BPE vocabulary for all languages, which is coupled with an
auxiliary decoder and tra... | 2018-12-26T18:58:39Z | TACL | null | 10.1162/tacl_a_00288 | null | null | null | null | null | null | null |
1,901.02446 | Panoptic Feature Pyramid Networks | ['Alexander Kirillov', 'Ross Girshick', 'Kaiming He', 'Piotr Dollár'] | ['cs.CV'] | The recently introduced panoptic segmentation task has renewed our
community's interest in unifying the tasks of instance segmentation (for thing
classes) and semantic segmentation (for stuff classes). However, current
state-of-the-art methods for this joint task use separate and dissimilar
networks for instance and se... | 2019-01-08T18:55:31Z | accepted to CVPR 2019 | null | null | Panoptic Feature Pyramid Networks | ['Alexander Kirillov', 'Ross B. Girshick', 'Kaiming He', 'Piotr Dollár'] | 2,019 | Computer Vision and Pattern Recognition | 1,295 | 62 | ['Computer Science'] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.