| --- |
| license: cc-by-4.0 |
| task_categories: |
| - object-detection |
| tags: |
| - RGB-D |
| - video-object-counting |
| - crowded-scenes |
| - occlusion |
| --- |
| |
| # RGBD-VideoCount |
|
|
| RGBD-VideoCount is an RGB-D video dataset for video object counting in crowded and occluded scenes. It provides synchronized RGB frames and depth maps, together with instance-level annotations for evaluating detection, cross-frame association, and video-level de-duplication. |
|
|
| ## Dataset Summary |
|
|
| - 195 RGB-D video clips |
| - 6 object categories |
| - 2,032 finely annotated frames |
| - 77,638 instance bounding boxes |
| - Multi-category shelf and crowded-object scenes |
| - RGB frames, aligned depth maps, instance annotations, counting annotations, data splits, and visual exemplars |
|
|
| ## Directory Structure |
|
|
| ```text |
| RGBD-VideoCount/ |
| |- images/ |
| |- Depth_Data/ |
| |- object_annotations/ |
| |- count_annotations/ |
| |- dataset_split.json |
| |- video_class.txt |
| |- exemplars_train.json |
| |- exemplars_val.json |
| `- exemplars_test.json |
| ``` |
|
|
| ## Data Description |
|
|
| - `images/`: RGB video frames. |
| - `Depth_Data/`: Depth maps aligned with RGB frames. |
| - `object_annotations/`: Instance-level bounding-box annotations. |
| - `count_annotations/`: Video-level counting annotations. |
| - `dataset_split.json`: Training, validation, and test splits. |
| - `video_class.txt`: Category metadata. |
| - `exemplars_*.json`: Visual exemplars for exemplar-guided training and evaluation. |
|
|
| ## Citation |
|
|
| If you use this code, please cite our paper: |
|
|
| ```bibtex |
| @inproceedings{xu2026depth, |
| title = {Depth-Guided Video Object Counting in Crowded Scenes}, |
| author = {Xu, Yuanjing and Liu, Xinyan and Chen, Weidong and Zou, Zixuan and Zhang, Linhao and Meng, Zhuangzhe and Chan, Antoni B. and Zhang, Weigang}, |
| booktitle = {Proceedings of the 34th ACM International Conference on Multimedia}, |
| year = {2026}, |
| doi = {10.1145/3767308.3835482} |
| } |
| ``` |
|
|
| ## Limitations |
|
|
| RGBD-VideoCount focuses on crowded object scenes and may not represent all real-world environments. Performance can be affected by depth quality, severe appearance ambiguity, camera motion, and unseen object categories. Users are responsible for evaluating suitability before deployment in real applications. |
|
|
| ## License |
|
|
| RGBD-VideoCount is released under the [Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/). Users must provide appropriate attribution when using, modifying, or redistributing this dataset. |
|
|
| ## Related Resources |
|
|
| - Model weights: https://huggingface.co/aerospace123/DG-Net |
| - Dataset: https://huggingface.co/datasets/aerospace123/RGBD-VideoCount |
| - Code: https://github.com/streamer-AP/DG-Net |
