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Human action generation

2 papers with code · Computer Vision

Yan et al. (2019) CSGN:

"When the dancer is stepping, jumping and spinning on the stage, attentions of all audiences are attracted by the streamof the fluent and graceful movements. Building a model that is capable of dancing is as fascinating a task as appreciating the performance itself. In this paper, we aim to generate long-duration human actions represented as skeleton sequences, e.g. those that cover the entirety of a dance, with hundreds of moves and countless possible combinations."

( Image credit: Convolutional Sequence Generation for Skeleton-Based Action Synthesis )


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Greatest papers with code

Convolutional Sequence Generation for Skeleton-Based Action Synthesis

ICCV 2019 2019 yysijie/CSGN

It captures the temporal structure at multiple scales through the GP prior and the temporal convolutions; and establishes the spatial connection between the latent vectors and the skeleton graphs via a novel graph refining scheme.


Human Action Generation with Generative Adversarial Networks

26 May 2018xingchenzhao/deep-learning-team-project

Inspired by the recent advances in generative models, we introduce a human action generation model in order to generate a consecutive sequence of human motions to formulate novel actions.