R2SM Dataset

Dataset preparation

1. COCOA-cls

Download COCO images (2014 Train images, 2014 Val images) from here.

2. D2SA

Download D2SA images from here.

3. MUVA

Download MUVA images from here.

Dataset format

Each split (cocoa-cls_split, d2sa_split, muva_split) follows the gRefCOCO format and contains three files:

1. instances.json
   • Contains all instance annotations
   • Mask format: RLE
   • Bounding box format: [x, y, width, height]
2. queries_amodal.json
   • Includes amodal queries only (as mentioned in the main paper).
   • Each entry links a query to the referred objects.
3. queries_all.json
   • Includes both amodal and modal queries.
   • Each entry links queries to the referred objects.

Source Attribution

The R2SM dataset is constructed using images and annotations adapted from the following publicly available datasets:

• COCOA-cls and D2SA: From Learning to See the Invisible: End-to-End Trainable Amodal Instance Segmentation (WACV 2019) by Follmann et al.
• MUVA: From MUVA: A New Large-Scale Benchmark for Multi-view Amodal Instance Segmentation in the Shopping Scenario (ICCV 2023) by Li et al.
  • Licensed under Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0).
  • License link: https://creativecommons.org/licenses/by-nc/4.0/

All images and annotations are originally released under non-commercial academic licenses, and R2SM is released under the same usage restriction. Please refer to the original datasets for full details.

Citations

If you use R2SM, please also cite the original sources:

@inproceedings{FollmannKHKB19,
  author       = {Patrick Follmann and Rebecca K{\"{o}}nig and Philipp H{\"{a}}rtinger and Michael Klostermann and Tobias B{\"{o}}ttger},
  title        = {Learning to See the Invisible: End-to-End Trainable Amodal Instance Segmentation},
  booktitle    = {{IEEE} Winter Conference on Applications of Computer Vision, {WACV} 2019, Waikoloa Village, HI, USA, January 7-11, 2019},
  year         = {2019}
}
@inproceedings{FollmannBHKU18,
  author       = {Patrick Follmann and Tobias B{\"{o}}ttger and Philipp H{\"{a}}rtinger and Rebecca K{\"{o}}nig and Markus Ulrich},
  editor       = {Vittorio Ferrari and Martial Hebert and Cristian Sminchisescu and Yair Weiss},
  title        = {MVTec {D2S:} Densely Segmented Supermarket Dataset},
  booktitle    = {Computer Vision - {ECCV} 2018 - 15th European Conference, Munich, Germany, September 8-14, 2018, Proceedings, Part {X}},
  series       = {Lecture Notes in Computer Science},
  year         = {2018}
}
@inproceedings{ZhuTMD17,
  author       = {Yan Zhu and Yuandong Tian and Dimitris N. Metaxas and Piotr Doll{\'{a}}r},
  title        = {Semantic Amodal Segmentation},
  booktitle    = {2017 {IEEE} Conference on Computer Vision and Pattern Recognition,
                  {CVPR} 2017, Honolulu, HI, USA, July 21-26, 2017},
  year         = {2017}
}
@inproceedings{LiYTBZJ023,
  author       = {Zhixuan Li and Weining Ye and Juan Terven and Zachary Bennett and Ying Zheng and Tingting Jiang and Tiejun Huang},
  title        = {{MUVA:} {A} New Large-Scale Benchmark for Multi-view Amodal Instance Segmentation in the Shopping Scenario},
  booktitle    = {{IEEE/CVF} International Conference on Computer Vision, {ICCV} 2023, Paris, France, October 1-6, 2023},
  year         = {2023}
}