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PointVST: Self-Supervised Pre-training for 3D Point Clouds via View-Specific Point-to-Image Translation
Qijian Zhang, Junhui Hou
The past few years have witnessed the great success and prevalence of self-supervised representation learning within the language and 2D vision communities. However, such advanceme…
Flattening-Net: Deep Regular 2D Representation for 3D Point Cloud Analysis
Qijian Zhang, Junhui Hou, Yue Qian +3
Point clouds are characterized by irregularity and unstructuredness, which pose challenges in efficient data exploitation and discriminative feature extraction. In this paper, we p…
Leveraging Single-View Images for Unsupervised 3D Point Cloud Completion
Lintai Wu, Qijian Zhang, Junhui Hou +1
Point clouds captured by scanning devices are often incomplete due to occlusion. To overcome this limitation, point cloud completion methods have been developed to predict the comp…
PointCA: Evaluating the Robustness of 3D Point Cloud Completion Models Against Adversarial Examples
Shengshan Hu, Junwei Zhang, Wei Liu +5
Point cloud completion, as the upstream procedure of 3D recognition and segmentation, has become an essential part of many tasks such as navigation and scene understanding. While v…
GeoUDF: Surface Reconstruction from 3D Point Clouds via Geometry-guided Distance Representation
Siyu Ren, Junhui Hou, Xiaodong Chen +2
We present a learning-based method, namely GeoUDF,to tackle the long-standing and challenging problem of reconstructing a discrete surface from a sparse point cloud.To be specific,…
EGRC-Net: Embedding-induced Graph Refinement Clustering Network
Zhihao Peng, Hui Liu, Yuheng Jia +1
Existing graph clustering networks heavily rely on a predefined yet fixed graph, which can lead to failures when the initial graph fails to accurately capture the data topology str…