312 citations · 610 across the 14 of their papers we have counts for
14 papers
Pixel2Mesh++: 3D Mesh Generation and Refinement from Multi-View Images
Chao Wen, Yinda Zhang, Chenjie Cao +3
We study the problem of shape generation in 3D mesh representation from a small number of color images with or without camera poses. While many previous works learn to hallucinate…
Video Depth Estimation by Fusing Flow-to-Depth Proposals
Jiaxin Xie, Chenyang Lei, Zhuwen Li +2
Depth from a monocular video can enable billions of devices and robots with a single camera to see the world in 3D. In this paper, we present an approach with a differentiable flow…
DeepSFM: Structure From Motion Via Deep Bundle Adjustment
Xingkui Wei, Yinda Zhang, Zhuwen Li +2
Structure from motion (SfM) is an essential computer vision problem which has not been well handled by deep learning. One of the promising trends is to apply explicit structural co…
Neural Point Cloud Rendering via Multi-Plane Projection
Peng Dai, Yinda Zhang, Zhuwen Li +2
We present a new deep point cloud rendering pipeline through multi-plane projections. The input to the network is the raw point cloud of a scene and the output are image or image s…
PointPWC-Net: A Coarse-to-Fine Network for Supervised and Self-Supervised Scene Flow Estimation on 3D Point Clouds
Wenxuan Wu, Zhiyuan Wang, Zhuwen Li +2
We propose a novel end-to-end deep scene flow model, called PointPWC-Net, on 3D point clouds in a coarse-to-fine fashion. Flow computed at the coarse level is upsampled and warped…
Deep Stereo using Adaptive Thin Volume Representation with Uncertainty Awareness
Shuo Cheng, Zexiang Xu, Shilin Zhu +4
We present Uncertainty-aware Cascaded Stereo Network (UCS-Net) for 3D reconstruction from multiple RGB images. Multi-view stereo (MVS) aims to reconstruct fine-grained scene geomet…
3D Rigid Motion Segmentation with Mixed and Unknown Number of Models
Xun Xu, Loong-Fah Cheong, Zhuwen Li
Many real-world video sequences cannot be conveniently categorized as general or degenerate; in such cases, imposing a false dichotomy in using the fundamental matrix or homography…
Pixel2Mesh++: Multi-View 3D Mesh Generation via Deformation
Chao Wen, Yinda Zhang, Zhuwen Li +1
We study the problem of shape generation in 3D mesh representation from a few color images with known camera poses. While many previous works learn to hallucinate the shape directl…
What Do Single-view 3D Reconstruction Networks Learn?
Maxim Tatarchenko, Stephan R. Richter, René Ranftl +3
Convolutional networks for single-view object reconstruction have shown impressive performance and have become a popular subject of research. All existing techniques are united by…
Learning for Multi-Type Subspace Clustering
Xun Xu, Loong-Fah Cheong, Zhuwen Li
Subspace clustering has been extensively studied from the hypothesis-and-test, algebraic, and spectral clustering based perspectives. Most assume that only a single type/class of s…
Learning for Multi-Model and Multi-Type Fitting
Xun Xu, Loong-Fah Cheong, Zhuwen Li
Multi-model fitting has been extensively studied from the random sampling and clustering perspectives. Most assume that only a single type/class of model is present and their gener…
Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search
Zhuwen Li, Qifeng Chen, Vladlen Koltun
We present a learning-based approach to computing solutions for certain NP-hard problems. Our approach combines deep learning techniques with useful algorithmic elements from class…
Motion Segmentation by Exploiting Complementary Geometric Models
Xun Xu, Loong-Fah Cheong, Zhuwen Li
Many real-world sequences cannot be conveniently categorized as general or degenerate; in such cases, imposing a false dichotomy in using the fundamental matrix or homography model…
Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images
Nanyang Wang, Yinda Zhang, Zhuwen Li +3
We propose an end-to-end deep learning architecture that produces a 3D shape in triangular mesh from a single color image. Limited by the nature of deep neural network, previous me…