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Toward Continuous-Time Representation of Human Motion

Weiyu Du, Oleh Rybkin, Lingzhi Zhang, Jianbo Shi
ECCV 2020 Workshop on Perception Through Structured Generative Models (http://generativeperception.com/)
link to paper
link to video presentation

Motion Reconstruction

Motion reconstruction on AMASS test set, from left to right: ground truth, reconstruction with Sine Motion Encoding, reconstruction with Bezier Motion Encoding.

Motion Generation

Point-to-point motion generation on AMASS test set (30 frames), from left to right: ground truth, prediction by Sine Motion Encoding, prediction by Bezier Motion Encoding, latent linear interpolation baseline.

Point-to-point motion generation on Human3.6M test set (sub-sampled 5 times, 30 frames), from left to right: ground truth, prediction by Sine Motion Encoding(6 curves), prediction by Sine Motion Encoding(3 curves), prediction by Bezier Motion Encoding, latent linear interpolation baseline.

Variable Frequency Motion Generation

Motion generation at different lengths and frame rates on Human3.6M test set using Sine Motion Encoding (3 curves), from left to right: ground truth (30 frames, fps=12), prediction (30 frames, fps=12), prediction (60 frames, fps=24).

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Toward Continuous-Time Representations of Human Motion | ECCV20 PTSGM Workshop | Demo Page

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