Self-attentive 3D human pose and shape estimation from videos

Author:

Chen Yun-ChunORCID,Piccirilli Marco,Piramuthu RobinsonORCID,Yang Ming-HsuanORCID

Funder

National Science Foundation

NSF

Publisher

Elsevier BV

Subject

Computer Vision and Pattern Recognition,Signal Processing,Software

Reference66 articles.

1. Posetrack: A benchmark for human pose estimation and tracking;Andriluka,2018

2. Exploiting temporal context for 3D human pose estimation in the wild;Arnab,2019

3. Bewley, A., Ge, Z., Ott, L., Ramos, F., Upcroft, B., 2016. Simple online and realtime tracking. In: ICIP.

4. YOLOv4: Optimal speed and accuracy of object detection;Bochkovskiy,2020

5. Bogo, F., Kanazawa, A., Lassner, C., Gehler, P., Romero, J., Black, M.J., 2016. Keep it SMPL: Automatic estimation of 3D human pose and shape from a single image. In: ECCV.

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3. FALNet: flow-based attention lightweight network for human pose estimation;Journal of Electronic Imaging;2023-09-13

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