activity
20162020
most citedVisually-Aware Fashion Recommendation and Design with Generative Image Models

32 citations · 84 across the 8 of their papers we have counts for

collaborators

17 papers

cs.CV202010 cited

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…

cs.CV2020

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…

cs.CV2019

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…

cs.IR20193 cited

Creative Procedural-Knowledge Extraction From Web Design Tutorials

Longqi Yang, Chen Fang, Hailin Jin +2

Complex design tasks often require performing diverse actions in a specific order. To (semi-)autonomously accomplish these tasks, applications need to understand and learn a wide r…

cs.CV2019

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…

cs.CV20191 cited

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…