Predicting people’s 3D poses from short sequences

We propose an efficient approach to exploiting motion information from consecutive frames of a video sequence to recover the 3D pose of people. Instead of computing candidate poses in individual frames and then linking them, as is often done, we regress directly from a spatio-temporal block of frames to a 3D pose in the central one. We will demonstrate that this approach allows us to effectively overcome ambiguities and to improve upon the state-of-the-art on challenging sequences.

PDF Abstract
No code implementations yet. Submit your code now

Datasets


Results from the Paper


Results from Other Papers


Task Dataset Model Metric Name Metric Value Rank Source Paper Compare
3D Human Pose Estimation Human3.6M Pyramid of 3D HOG features Average MPJPE (mm) 125.28 # 330

Methods


No methods listed for this paper. Add relevant methods here