17 citations · 41 across the 7 of their papers we have counts for
7 papers
Clutter Detection and Removal in 3D Scenes with View-Consistent Inpainting
Fangyin Wei, Thomas Funkhouser, Szymon Rusinkiewicz
Removing clutter from scenes is essential in many applications, ranging from privacy-concerned content filtering to data augmentation. In this work, we present an automatic system…
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…
Integral Human Pose Regression
Xiao Sun, Bin Xiao, Fangyin Wei +2
State-of-the-art human pose estimation methods are based on heat map representation. In spite of the good performance, the representation has a few issues in nature, such as not di…
Recurrent Scale Approximation for Object Detection in CNN
Yu Liu, Hongyang Li, Junjie Yan +3
Since convolutional neural network (CNN) lacks an inherent mechanism to handle large scale variations, we always need to compute feature maps multiple times for multi-scale object…