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Implementation of joint construction of Mask/BBox heads in QDTrack-mots for joint training research
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jkd2021/joint-QDTrack
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SAIL-VOS & SAIL-VOScut (videos split into video-cuts without abrupt scene change)
amodal annotations: visible annotations:
Using joint construction of the functional heads (Mask Heads / BBox Heads) in the original Mask R-CNN architecture ofQDTrack-mots for joint training research.
QDTrack-mots-joint testing results:
amodal results: visible results:
QDTrack-mots-joint+ testing results:
amodal results: visible results:
Please refer toQDTrack for details of (Amodal)QDTrack-mots
Please refer toPCAN for details of (Amodal)PCAN
@inproceedings{hu2019sail, title={Sail-vos: Semantic amodal instance level video object segmentation-a synthetic dataset and baselines}, author={Hu, Yuan-Ting and Chen, Hong-Shuo and Hui, Kexin and Huang, Jia-Bin and Schwing, Alexander G}, booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, pages={3105--3115}, year={2019}}@inproceedings{pang2021quasi, title={Quasi-dense similarity learning for multiple object tracking}, author={Pang, Jiangmiao and Qiu, Linlu and Li, Xia and Chen, Haofeng and Li, Qi and Darrell, Trevor and Yu, Fisher}, booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition}, pages={164--173}, year={2021}}@inproceedings{pcan, title={Prototypical Cross-Attention Networks for Multiple Object Tracking and Segmentation}, author={Ke, Lei and Li, Xia and Danelljan, Martin and Tai, Yu-Wing and Tang, Chi-Keung and Yu, Fisher}, booktitle={Advances in Neural Information Processing Systems}, year={2021}}