28 citations · 117 across the 17 of their papers we have counts for
10 papers · 1 filter
SCORES: Shape Composition with Recursive Substructure Priors
Chenyang Zhu, Kai Xu, Siddhartha Chaudhuri +2
We introduce SCORES, a recursive neural network for shape composition. Our network takes as input sets of parts from two or more source 3D shapes and a rough initial placement of t…
Learning to Group and Label Fine-Grained Shape Components
Xiaogang Wang, Bin Zhou, Haiyue Fang +3
A majority of stock 3D models in modern shape repositories are assembled with many fine-grained components. The main cause of such data form is the component-wise modeling process…
VERAM: View-Enhanced Recurrent Attention Model for 3D Shape Classification
Songle Chen, Lintao Zheng, Yan Zhang +2
Multi-view deep neural network is perhaps the most successful approach in 3D shape classification. However, the fusion of multi-view features based on max or average pooling lacks…
Triangle Lasso for Simultaneous Clustering and Optimization in Graph Datasets
Yawei Zhao, Kai Xu, Xinwang Liu +3
Recently, network lasso has drawn many attentions due to its remarkable performance on simultaneous clustering and optimization. However, it usually suffers from the imperfect data…
Learning Discriminative 3D Shape Representations by View Discerning Networks
Biao Leng, Cheng Zhang, Xiaocheng Zhou +2
In view-based 3D shape recognition, extracting discriminative visual representation of 3D shapes from projected images is considered the core problem. Projections with low discrimi…
Caging Loops in Shape Embedding Space: Theory and Computation
Jian Liu, Shiqing Xin, Zengfu Gao +3
We propose to synthesize feasible caging grasps for a target object through computing Caging Loops, a closed curve defined in the shape embedding space of the object. Different fro…