17 citations · 29 across the 3 of their papers we have counts for
4 papers
InMoDeGAN: Interpretable Motion Decomposition Generative Adversarial Network for Video Generation
Yaohui Wang, Francois Bremond, Antitza Dantcheva
In this work, we introduce an unconditional video generative model, InMoDeGAN, targeted to (a) generate high quality videos, as well as to (b) allow for interpretation of the laten…
Joint Generative and Contrastive Learning for Unsupervised Person Re-identification
Hao Chen, Yaohui Wang, Benoit Lagadec +2
Recent self-supervised contrastive learning provides an effective approach for unsupervised person re-identification (ReID) by learning invariance from different views (transformed…
Selective Spatio-Temporal Aggregation Based Pose Refinement System: Towards Understanding Human Activities in Real-World Videos
Di Yang, Rui Dai, Yaohui Wang +4
Taking advantage of human pose data for understanding human activities has attracted much attention these days. However, state-of-the-art pose estimators struggle in obtaining high…
G3AN: Disentangling Appearance and Motion for Video Generation
Yaohui Wang, Piotr Bilinski, Francois Bremond +1
Creating realistic human videos entails the challenge of being able to simultaneously generate both appearance, as well as motion. To tackle this challenge, we introduce GAN,…