Update README.md

README.md

@@ -31,17 +31,13 @@ tags:
 
 # 🏙️ Urban-ImageNet
 
-**A Large-Scale Multi-Modal Dataset and Evaluation Framework for Urban Space Perception from User-generated Social Media Imagery.**
+**A Large-Scale Multi-Modal Dataset and Evaluation Framework for Urban Space Perception from Social Media Imagery.**
 
 <p align="center">
   <a href="https://arxiv.org/abs/2605.09936"><img src="https://img.shields.io/badge/arXiv-2605.09936-b31b1b.svg" alt="arXiv"/></a>
   <a href="https://github.com/yiasun/dataset-2"><img src="https://img.shields.io/badge/GitHub-yiasun%2Fdataset--2-black?logo=github" alt="GitHub"/></a>
   <a href="https://huggingface.co/datasets/yiasun/urban-imagenet"><img src="https://img.shields.io/badge/🤗%20HuggingFace-Dataset-yellow" alt="HuggingFace"/></a>
-  <img src="https://img.shields.io/badge/License-CC%20BY--NC--SA%204.0-lightgrey" alt="License"/>
-  <img src="https://img.shields.io/badge/Images-2M%2B-blue" alt="Scale"/>
-  <img src="https://img.shields.io/badge/Cities-24-green" alt="Cities"/>
 </p>
-
 > Urban-ImageNet fills a critical gap between computer vision and urban studies by treating cities not simply as visual scenes, but as lived, socially produced, and experientially activated spaces.
 
 ---
@@ -61,7 +57,6 @@ The corpus contains over **2 million** public Weibo image–text pairs collected
 | **T2** | Cross-modal image–text retrieval    | Image ↔ Text (bidirectional)          |
 | **T3** | Instance segmentation               | Image → Object masks + bounding boxes |
 
-<!-- Replace the path below with the actual uploaded framework figure -->
 ![Urban-ImageNet Framework Overview](Figures/01-Overall-Framework.jpg)
 *Figure 1: The Urban-ImageNet framework — addressing current limitations in urban perception evaluation. The dataset bridges general-purpose vision benchmarks and domain-specific urban research needs through the HUSIC taxonomy and three unified benchmark tasks.*
 
@@ -553,10 +548,10 @@ Urban-ImageNet is derived from **public Weibo posts** — posts whose visibility
 If you use Urban-ImageNet in your research, please cite our paper:
 
 ```bibtex
-@misc{ou2026urbanimagenet,
+@article{ou2026urbanimagenet,
   title   = {Urban-ImageNet: A Large-Scale Multi-Modal Dataset and Evaluation Framework for Urban Space Perception},
-  author  = {Yiwei Ou and Chung Ching Cheung and Jun Yang Ang and Xiaobin Ren and
-             Ronggui Sun and Guansong Gao and Kaiqi Zhao and Manfredo Manfredini},
+  author  = {Ou, Yiwei and Cheung, Chung Ching and Ang, Jun Yang and Ren, Xiaobin and Sun, Ronggui and Gao, Guansong and Zhao, Kaiqi and Manfredini, Manfredo},
+  journal = {arXiv preprint arXiv:2605.09936},
   year    = {2026},
   eprint  = {2605.09936},
   archivePrefix = {arXiv},
@@ -588,8 +583,8 @@ Urban-ImageNet is designed as a **domain-specific complement** to the following
 
 ## License
 
-The dataset is released under **Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)**.
+The dataset is released under **Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)**.
 
-You are free to use, share, and adapt this dataset for **non-commercial academic research** with appropriate attribution. Commercial use of any kind is prohibited.
+You are free to use, share, and adapt this dataset for **non-commercial academic research** with appropriate attribution, provided that you give appropriate credit and distribute any derivative works under the same license. Commercial use of any kind is prohibited.
 
-See [LICENSE](https://creativecommons.org/licenses/by-nc/4.0/) for full terms.
+See [LICENSE](https://creativecommons.org/licenses/by-nc-sa/4.0/) for full terms.