53 citations · 207 across the 11 of their papers we have counts for
4 papers · 2 filters
Large-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55
Li Yi, Lin Shao, Manolis Savva +47
We introduce a large-scale 3D shape understanding benchmark using data and annotation from ShapeNet 3D object database. The benchmark consists of two tasks: part-level segmentation…
High-Resolution Shape Completion Using Deep Neural Networks for Global Structure and Local Geometry Inference
Xiaoguang Han, Zhen Li, Haibin Huang +2
We propose a data-driven method for recovering miss-ing parts of 3D shapes. Our method is based on a new deep learning architecture consisting of two sub-networks: a global structu…
3D Shape Reconstruction from Sketches via Multi-view Convolutional Networks
Zhaoliang Lun, Matheus Gadelha, Evangelos Kalogerakis +2
We propose a method for reconstructing 3D shapes from 2D sketches in the form of line drawings. Our method takes as input a single sketch, or multiple sketches, and outputs a dense…
Learning Local Shape Descriptors from Part Correspondences With Multi-view Convolutional Networks
Haibin Huang, Evangelos Kalogerakis, Siddhartha Chaudhuri +3
We present a new local descriptor for 3D shapes, directly applicable to a wide range of shape analysis problems such as point correspondences, semantic segmentation, affordance pre…