The dataset viewer is not available for this subset.
Exception: ConnectionError
Message: Couldn't reach 'EPFL-VILAB/TST-Replica' on the Hub (ReadTimeout)
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 65, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 268, in get_dataset_config_info
builder = load_dataset_builder(
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1315, in load_dataset_builder
dataset_module = dataset_module_factory(
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1207, in dataset_module_factory
raise e1 from None
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1149, in dataset_module_factory
raise ConnectionError(f"Couldn't reach '{path}' on the Hub ({e.__class__.__name__})") from e
ConnectionError: Couldn't reach 'EPFL-VILAB/TST-Replica' on the Hub (ReadTimeout)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Dataset Card for TST-Replica
Dataset Summary
This custom TST-Replica dataset is used in research work "Multimodality as Supervision: Self-Supervised Specialization to the Test Environment via Multimodality".
pretrain/is a multimodal pretraining dataset collected using Replica simulation environment. It contains RGB images, and 9 additional tokenized modalities.segmentation/trainis the associated downstream dataset used to finetune TST pretrained models on semantic segmentation tasks.segmentation/testcontains the test dataset used for evaluation/testing on semantic segmentation task. This data corresponds to samples obtained from the test-space itself.
Dataset Structure Pretraining Data
TST-Replica/
├── pretrain/
│ ├── test_spaces/
│ │ ├── crop_settings/ # Contains .tar shards
│ │ ├── det/ # Contains .tar shards
│ │ ├── rgb/ # Contains .tar shards
│ │ ├── tok_canny_edge@224/ # Contains .tar shards
│ │ ├── ... # More tokenized feature directories
│ │ └── tok_semseg@224/ # Contains .tar shards
│ └── transfer/
│ ├── crop_settings/ # Contains .tar shards
│ ├── det/ # Contains .tar shards
│ ├── rgb/ # Contains .tar shards
│ ├── tok_canny_edge@224/ # Contains .tar shards
│ ├── ... # More tokenized feature directories
│ └── tok_semseg@224/ # Contains .tar shards
├── segmentation/
│ ├── train/ # Training data for segmentation
│ └── test/ # Test data for segmentation
└── README.md
Dataset Creation
We use Omnidata, to densely sample Replica meshes corresponding to the 5 scenes to build our pre-training dataset. We defer the details of the sampling procedure to Omnidata.
Source Data
Original dataset samples are collected from Omnidata framework.
Citation Information
@inproceedings{singh2026tst,
title={Multimodality as Supervision: Self-Supervised Specialization to the Test Environment via Multimodality},
author={Kunal Pratap Singh and Ali Garjani and Rishubh Singh and Muhammad Uzair Khattak and Efe Tarhan and Jason Toskov and Andrei Atanov and O{\u{g}}uzhan Fatih Kar and Amir Zamir},
booktitle={International Conference on Learning Representations (ICLR)},
year={2026}
}
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