RGBD-VideoCount / README.md
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metadata
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

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:

@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. Users must provide appropriate attribution when using, modifying, or redistributing this dataset.

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