203 citations · 1.5k across the 53 of their papers we have counts for
9 papers · 1 filter
Single image reflection removal via learning with multi-image constraints
Yingda Yin, Qingnan Fan, Dongdong Chen +5
Reflections are very common phenomena in our daily photography, which distract people's attention from the scene behind the glass. The problem of removing reflection artifacts is i…
AutoRemover: Automatic Object Removal for Autonomous Driving Videos
Rong Zhang, Wei Li, Peng Wang +7
Motivated by the need for photo-realistic simulation in autonomous driving, in this paper we present a video inpainting algorithm \emph{AutoRemover}, designed specifically for gene…
Decoupling Features and Coordinates for Few-shot RGB Relocalization
Siyan Dong, Songyin Wu, Yixin Zhuang +3
Cross-scene model adaption is crucial for camera relocalization in real scenarios. It is often preferable that a pre-learned model can be fast adapted to a novel scene with as few…
PQ-NET: A Generative Part Seq2Seq Network for 3D Shapes
Rundi Wu, Yixin Zhuang, Kai Xu +2
We introduce PQ-NET, a deep neural network which represents and generates 3D shapes via sequential part assembly. The input to our network is a 3D shape segmented into parts, where…
DLGAN: Disentangling Label-Specific Fine-Grained Features for Image Manipulation
Guanqi Zhan, Yihao Zhao, Bingchan Zhao +3
Recent studies have shown how disentangling images into content and feature spaces can provide controllable image translation/ manipulation. In this paper, we propose a framework t…
Learning Elastic Constitutive Material and Damping Models
Bin Wang, Yuanmin Deng, Paul Kry +3
Commonly used linear and nonlinear constitutive material models in deformation simulation contain many simplifications and only cover a tiny part of possible material behavior. In…
A General Decoupled Learning Framework for Parameterized Image Operators
Qingnan Fan, Dongdong Chen, Lu Yuan +3
Many different deep networks have been used to approximate, accelerate or improve traditional image operators. Among these traditional operators, many contain parameters which need…
Learning Character-Agnostic Motion for Motion Retargeting in 2D
Kfir Aberman, Rundi Wu, Dani Lischinski +2
Analyzing human motion is a challenging task with a wide variety of applications in computer vision and in graphics. One such application, of particular importance in computer anim…
Unpaired Point Cloud Completion on Real Scans using Adversarial Training
Xuelin Chen, Baoquan Chen, Niloy J. Mitra
As 3D scanning solutions become increasingly popular, several deep learning setups have been developed geared towards that task of scan completion, i.e., plausibly filling in regio…