5 citations · 13 across the 6 of their papers we have counts for
13 papers
WarpingGAN: Warping Multiple Uniform Priors for Adversarial 3D Point Cloud Generation
Yingzhi Tang, Yue Qian, Qijian Zhang +3
We propose WarpingGAN, an effective and efficient 3D point cloud generation network. Unlike existing methods that generate point clouds by directly learning the mapping functions b…
IDEA-Net: Dynamic 3D Point Cloud Interpolation via Deep Embedding Alignment
Yiming Zeng, Yue Qian, Qijian Zhang +3
This paper investigates the problem of temporally interpolating dynamic 3D point clouds with large non-rigid deformation. We formulate the problem as estimation of point-wise traje…
ParaNet: Deep Regular Representation for 3D Point Clouds
Qijian Zhang, Junhui Hou, Yue Qian +2
Although convolutional neural networks have achieved remarkable success in analyzing 2D images/videos, it is still non-trivial to apply the well-developed 2D techniques in regular…
CorrNet3D: Unsupervised End-to-end Learning of Dense Correspondence for 3D Point Clouds
Yiming Zeng, Yue Qian, Zhiyu Zhu +3
Motivated by the intuition that one can transform two aligned point clouds to each other more easily and meaningfully than a misaligned pair, we propose CorrNet3D -- the first unsu…
MOPS-Net: A Matrix Optimization-driven Network forTask-Oriented 3D Point Cloud Downsampling
Yue Qian, Junhui Hou, Qijian Zhang +3
This paper explores the problem of task-oriented downsampling over 3D point clouds, which aims to downsample a point cloud while maintaining the performance of subsequent applicati…
PUGeo-Net: A Geometry-centric Network for 3D Point Cloud Upsampling
Yue Qian, Junhui Hou, Sam Kwong +1
This paper addresses the problem of generating uniform dense point clouds to describe the underlying geometric structures from given sparse point clouds. Due to the irregular and u…