activity
20182022
most citedProgressive Point Cloud Deconvolution Generation Network

8 citations · 16 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CV20221 cited

OTFace: Hard Samples Guided Optimal Transport Loss for Deep Face Representation

Jianjun Qian, Shumin Zhu, Chaoyu Zhao +2

Face representation in the wild is extremely hard due to the large scale face variations. To this end, some deep convolutional neural networks (CNNs) have been developed to learn d…

cs.CV2022

Cross-View Panorama Image Synthesis

Songsong Wu, Hao Tang, Xiao-Yuan Jing +4

In this paper, we tackle the problem of synthesizing a ground-view panorama image conditioned on a top-view aerial image, which is a challenging problem due to the large gap betwee…

cs.CV20213 cited

Sampling Network Guided Cross-Entropy Method for Unsupervised Point Cloud Registration

Haobo Jiang, Yaqi Shen, Jin Xie +3

In this paper, by modeling the point cloud registration task as a Markov decision process, we propose an end-to-end deep model embedded with the cross-entropy method (CEM) for unsu…

cs.CV20212 cited

Planning with Learned Dynamic Model for Unsupervised Point Cloud Registration

Haobo Jiang, Jin Xie, Jianjun Qian +1

Point cloud registration is a fundamental problem in 3D computer vision. In this paper, we cast point cloud registration into a planning problem in reinforcement learning, which ca…

cs.CV20208 cited

Progressive Point Cloud Deconvolution Generation Network

Le Hui, Rui Xu, Jin Xie +2

In this paper, we propose an effective point cloud generation method, which can generate multi-resolution point clouds of the same shape from a latent vector. Specifically, we deve…

cs.CV20192 cited

Structured Discriminative Tensor Dictionary Learning for Unsupervised Domain Adaptation

Songsong Wu, Yan Yan, Hao Tang +3

Unsupervised Domain Adaptation (UDA) addresses the problem of performance degradation due to domain shift between training and testing sets, which is common in computer vision appl…