14 citations · 25 across the 15 of their papers we have counts for
7 papers · 1 filter
SOCS: Semantically-aware Object Coordinate Space for Category-Level 6D Object Pose Estimation under Large Shape Variations
Boyan Wan, Yifei Shi, Kai Xu
Most learning-based approaches to category-level 6D pose estimation are design around normalized object coordinate space (NOCS). While being successful, NOCS-based methods become i…
Deep Graph-based Spatial Consistency for Robust Non-rigid Point Cloud Registration
Zheng Qin, Hao Yu, Changjian Wang +2
We study the problem of outlier correspondence pruning for non-rigid point cloud registration. In rigid registration, spatial consistency has been a commonly used criterion to disc…
NEF: Neural Edge Fields for 3D Parametric Curve Reconstruction from Multi-view Images
Yunfan Ye, Renjiao Yi, Zhirui Gao +3
We study the problem of reconstructing 3D feature curves of an object from a set of calibrated multi-view images. To do so, we learn a neural implicit field representing the densit…
Edge Preserving Implicit Surface Representation of Point Clouds
Xiaogang Wang, Yuhang Cheng, Liang Wang +3
Learning implicit surface directly from raw data recently has become a very attractive representation method for 3D reconstruction tasks due to its excellent performance. However,…
AutoTransition: Learning to Recommend Video Transition Effects
Yaojie Shen, Libo Zhang, Kai Xu +1
Video transition effects are widely used in video editing to connect shots for creating cohesive and visually appealing videos. However, it is challenging for non-professionals to…
RIM-Net: Recursive Implicit Fields for Unsupervised Learning of Hierarchical Shape Structures
Chengjie Niu, Manyi Li, Kai Xu +1
We introduce RIM-Net, a neural network which learns recursive implicit fields for unsupervised inference of hierarchical shape structures. Our network recursively decomposes an inp…