3D Human Dynamics

3 papers with code • 0 benchmarks • 1 datasets

Image: Zhang et al


Most implemented papers

Learning 3D Human Dynamics from Video

akanazawa/human_dynamics CVPR 2019

We present a framework that can similarly learn a representation of 3D dynamics of humans from video via a simple but effective temporal encoding of image features.

Predicting 3D Human Dynamics from Video

jasonyzhang/phd ICCV 2019

In this work, we present perhaps the first approach for predicting a future 3D mesh model sequence of a person from past video input.

Dynamical Variational Autoencoders: A Comprehensive Review

XiaoyuBIE1994/DVAE 28 Aug 2020

Recently, a series of papers have presented different extensions of the VAE to process sequential data, which model not only the latent space but also the temporal dependencies within a sequence of data vectors and corresponding latent vectors, relying on recurrent neural networks or state-space models.