98 citations · 178 across the 16 of their papers we have counts for
16 papers
Self-Supervised 3D Scene Flow Estimation Guided by Superpoints
Yaqi Shen, Le Hui, Jin Xie +1
3D scene flow estimation aims to estimate point-wise motions between two consecutive frames of point clouds. Superpoints, i.e., points with similar geometric features, are usually…
Learning Inter-Superpoint Affinity for Weakly Supervised 3D Instance Segmentation
Linghua Tang, Le Hui, Jin Xie
Due to the few annotated labels of 3D point clouds, how to learn discriminative features of point clouds to segment object instances is a challenging problem. In this paper, we pro…
Unsupervised Domain Adaptation for Point Cloud Semantic Segmentation via Graph Matching
Yikai Bian, Le Hui, Jianjun Qian +1
Unsupervised domain adaptation for point cloud semantic segmentation has attracted great attention due to its effectiveness in learning with unlabeled data. Most of existing method…
Generative Subgraph Contrast for Self-Supervised Graph Representation Learning
Yuehui Han, Le Hui, Haobo Jiang +2
Contrastive learning has shown great promise in the field of graph representation learning. By manually constructing positive/negative samples, most graph contrastive learning meth…
3D Siamese Transformer Network for Single Object Tracking on Point Clouds
Le Hui, Lingpeng Wang, Linghua Tang +3
Siamese network based trackers formulate 3D single object tracking as cross-correlation learning between point features of a template and a search area. Due to the large appearance…
RA-Depth: Resolution Adaptive Self-Supervised Monocular Depth Estimation
Mu He, Le Hui, Yikai Bian +3
Existing self-supervised monocular depth estimation methods can get rid of expensive annotations and achieve promising results. However, these methods suffer from severe performanc…