508 citations · 1.8k across the 23 of their papers we have counts for
6 papers · 1 filter
Dancing to Music
Hsin-Ying Lee, Xiaodong Yang, Ming-Yu Liu +4
Dancing to music is an instinctive move by humans. Learning to model the music-to-dance generation process is, however, a challenging problem. It requires significant efforts to me…
Few-shot Video-to-Video Synthesis
Ting-Chun Wang, Ming-Yu Liu, Andrew Tao +3
Video-to-video synthesis (vid2vid) aims at converting an input semantic video, such as videos of human poses or segmentation masks, to an output photorealistic video. While the sta…
Few-Shot Unsupervised Image-to-Image Translation
Ming-Yu Liu, Xun Huang, Arun Mallya +4
Unsupervised image-to-image translation methods learn to map images in a given class to an analogous image in a different class, drawing on unstructured (non-registered) datasets o…
STEP: Spatio-Temporal Progressive Learning for Video Action Detection
Xitong Yang, Xiaodong Yang, Ming-Yu Liu +3
In this paper, we propose Spatio-TEmporal Progressive (STEP) action detector---a progressive learning framework for spatio-temporal action detection in videos. Starting from a hand…
Joint Discriminative and Generative Learning for Person Re-identification
Zhedong Zheng, Xiaodong Yang, Zhiding Yu +3
Person re-identification (re-id) remains challenging due to significant intra-class variations across different cameras. Recently, there has been a growing interest in using genera…
Towards annotation-efficient segmentation via image-to-image translation
Eugene Vorontsov, Pavlo Molchanov, Christopher Beckham +2
Often in medical imaging, it is prohibitively challenging to produce enough boundary annotations to train deep neural networks for accurate tumor segmentation. We propose the use o…