60 citations · 131 across the 8 of their papers we have counts for
6 papers · 1 filter
Recurrent Slice Networks for 3D Segmentation of Point Clouds
Qiangui Huang, Weiyue Wang, Ulrich Neumann
Point clouds are an efficient data format for 3D data. However, existing 3D segmentation methods for point clouds either do not model local dependencies \cite{pointnet} or require…
Learning to Prune Filters in Convolutional Neural Networks
Qiangui Huang, Kevin Zhou, Suya You +1
Many state-of-the-art computer vision algorithms use large scale convolutional neural networks (CNNs) as basic building blocks. These CNNs are known for their huge number of parame…
Shape Inpainting using 3D Generative Adversarial Network and Recurrent Convolutional Networks
Weiyue Wang, Qiangui Huang, Suya You +2
Recent advances in convolutional neural networks have shown promising results in 3D shape completion. But due to GPU memory limitations, these methods can only produce low-resoluti…
SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation
Weiyue Wang, Ronald Yu, Qiangui Huang +1
We introduce Similarity Group Proposal Network (SGPN), a simple and intuitive deep learning framework for 3D object instance segmentation on point clouds. SGPN uses a single networ…
Automatic Vertebra Labeling in Large-Scale 3D CT using Deep Image-to-Image Network with Message Passing and Sparsity Regularization
Dong Yang, Tao Xiong, Daguang Xu +10
Automatic localization and labeling of vertebra in 3D medical images plays an important role in many clinical tasks, including pathological diagnosis, surgical planning and postope…
Scene Labeling using Gated Recurrent Units with Explicit Long Range Conditioning
Qiangui Huang, Weiyue Wang, Kevin Zhou +2
Recurrent neural network (RNN), as a powerful contextual dependency modeling framework, has been widely applied to scene labeling problems. However, this work shows that directly a…