Bootstrapping Human Optical Flow and Pose


Overview of Supplementary Material

In this supplementary material, we provide:
  1. Additional qualitative highlights of our method.
  2. Supplementary appendix which contains ablation study.

Abstract:

We propose a bootstrapping framework to enhance human optical flow and pose. We show that, for videos involving humans in scenes, we can improve both the optical flow and the pose estimation quality of humans by considering the two tasks at the same time. We enhance optical flow estimates by fine-tuning them to fit the human pose estimates and vice versa. In more detail, we optimize the pose and optical flow networks to, at inference time, agree with each other. We show that this results in state-of-the-art results on the Human 3.6M and 3D Poses in the Wild datasets, as well as a human-related subset of the Sintel dataset, both in terms of pose estimation accuracy and the optical flow accuracy at human joint locations.


Additional Qualitative Highlights

Qualitative Highlights of Optical Flow:

We demonstrate how our method improves optical flow estimates via bootstrapping it with human pose estimation.




Qualitative Highlights of Human Pose:

We further show how our method improves human pose estimation with the help of optical flow.






Supplementary Appendix

Ablation study in supplementary appendix. For more details, Click the image below to access the PDF

Supplementary Appendix PDF



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