1 citations · 2 across the 3 of their papers we have counts for
4 papers
Self-supervised Neural Articulated Shape and Appearance Models
Fangyin Wei, Rohan Chabra, Lingni Ma +6
Learning geometry, motion, and appearance priors of object classes is important for the solution of a large variety of computer vision problems. While the majority of approaches ha…
Learning to Infer Semantic Parameters for 3D Shape Editing
Fangyin Wei, Elena Sizikova, Avneesh Sud +2
Many applications in 3D shape design and augmentation require the ability to make specific edits to an object's semantic parameters (e.g., the pose of a person's arm or the length…
ADA-Tucker: Compressing Deep Neural Networks via Adaptive Dimension Adjustment Tucker Decomposition
Zhisheng Zhong, Fangyin Wei, Zhouchen Lin +1
Despite the recent success of deep learning models in numerous applications, their widespread use on mobile devices is seriously impeded by storage and computational requirements.…
Exploring Disentangled Feature Representation Beyond Face Identification
Yu Liu, Fangyin Wei, Jing Shao +3
This paper proposes learning disentangled but complementary face features with minimal supervision by face identification. Specifically, we construct an identity Distilling and Dis…