32 citations · 84 across the 8 of their papers we have counts for
14 papers · 1 filter
Human Motion Transfer from Poses in the Wild
Jian Ren, Menglei Chai, Sergey Tulyakov +3
In this paper, we tackle the problem of human motion transfer, where we synthesize novel motion video for a target person that imitates the movement from a reference video. It is a…
Anatomy-aware 3D Human Pose Estimation with Bone-based Pose Decomposition
Tianlang Chen, Chen Fang, Xiaohui Shen +3
In this work, we propose a new solution to 3D human pose estimation in videos. Instead of directly regressing the 3D joint locations, we draw inspiration from the human skeleton an…
EnlightenGAN: Deep Light Enhancement without Paired Supervision
Yifan Jiang, Xinyu Gong, Ding Liu +6
Deep learning-based methods have achieved remarkable success in image restoration and enhancement, but are they still competitive when there is a lack of paired training data? As o…
Multimodal Style Transfer via Graph Cuts
Yulun Zhang, Chen Fang, Yilin Wang +4
An assumption widely used in recent neural style transfer methods is that image styles can be described by global statics of deep features like Gram or covariance matrices. Alterna…
Dance Dance Generation: Motion Transfer for Internet Videos
Yipin Zhou, Zhaowen Wang, Chen Fang +2
This work presents computational methods for transferring body movements from one person to another with videos collected in the wild. Specifically, we train a personalized model o…
Im2Pencil: Controllable Pencil Illustration from Photographs
Yijun Li, Chen Fang, Aaron Hertzmann +2
We propose a high-quality photo-to-pencil translation method with fine-grained control over the drawing style. This is a challenging task due to multiple stroke types (e.g., outlin…