2.9k citations · 10.7k across the 136 of their papers we have counts for
7 papers · 1 filter
Frustum PointNets for 3D Object Detection from RGB-D Data
Charles R. Qi, Wei Liu, Chenxia Wu +2
In this work, we study 3D object detection from RGB-D data in both indoor and outdoor scenes. While previous methods focus on images or 3D voxels, often obscuring natural 3D patter…
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…
ComplementMe: Weakly-Supervised Component Suggestions for 3D Modeling
Minhyuk Sung, Hao Su, Vladimir G. Kim +2
Assembly-based tools provide a powerful modeling paradigm for non-expert shape designers. However, choosing a component from a large shape repository and aligning it to a partial a…
Learning Representations and Generative Models for 3D Point Clouds
Panos Achlioptas, Olga Diamanti, Ioannis Mitliagkas +1
Three-dimensional geometric data offer an excellent domain for studying representation learning and generative modeling. In this paper, we look at geometric data represented as poi…
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
Charles R. Qi, Li Yi, Hao Su +1
Few prior works study deep learning on point sets. PointNet by Qi et al. is a pioneer in this direction. However, by design PointNet does not capture local structures induced by th…
GRASS: Generative Recursive Autoencoders for Shape Structures
Jun Li, Kai Xu, Siddhartha Chaudhuri +3
We introduce a novel neural network architecture for encoding and synthesis of 3D shapes, particularly their structures. Our key insight is that 3D shapes are effectively character…