85 citations · 482 across the 58 of their papers we have counts for
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Generative Hierarchical Features from Synthesizing Images
Yinghao Xu, Yujun Shen, Jiapeng Zhu +2
Generative Adversarial Networks (GANs) have recently advanced image synthesis by learning the underlying distribution of the observed data. However, how the features learned from s…
Unsupervised Landmark Learning from Unpaired Data
Yinghao Xu, Ceyuan Yang, Ziwei Liu +2
Recent attempts for unsupervised landmark learning leverage synthesized image pairs that are similar in appearance but different in poses. These methods learn landmarks by encourag…
Video Representation Learning with Visual Tempo Consistency
Ceyuan Yang, Yinghao Xu, Bo Dai +1
Visual tempo, which describes how fast an action goes, has shown its potential in supervised action recognition. In this work, we demonstrate that visual tempo can also serve as a…
InterFaceGAN: Interpreting the Disentangled Face Representation Learned by GANs
Yujun Shen, Ceyuan Yang, Xiaoou Tang +1
Although Generative Adversarial Networks (GANs) have made significant progress in face synthesis, there lacks enough understanding of what GANs have learned in the latent represent…
Temporal Pyramid Network for Action Recognition
Ceyuan Yang, Yinghao Xu, Jianping Shi +2
Visual tempo characterizes the dynamics and the temporal scale of an action. Modeling such visual tempos of different actions facilitates their recognition. Previous works often ca…