activity
20212024
most citedSRPCN: Structure Retrieval based Point Completion Network

4 citations · 4 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2024

ELiTe: Efficient Image-to-LiDAR Knowledge Transfer for Semantic Segmentation

Zhibo Zhang, Ximing Yang, Weizhong Zhang +1

Cross-modal knowledge transfer enhances point cloud representation learning in LiDAR semantic segmentation. Despite its potential, the \textit{weak teacher challenge} arises due to…

cs.CV2024

Robust Fine-tuning for Pre-trained 3D Point Cloud Models

Zhibo Zhang, Ximing Yang, Weizhong Zhang +1

This paper presents a robust fine-tuning method designed for pre-trained 3D point cloud models, to enhance feature robustness in downstream fine-tuned models. We highlight the limi…

cs.CV2023

Point Cloud Part Editing: Segmentation, Generation, Assembly, and Selection

Kaiyi Zhang, Yang Chen, Ximing Yang +2

Ideal part editing should guarantee the diversity of edited parts, the fidelity to the remaining parts, and the quality of the results. However, previous methods do not disentangle…

cs.CV2022★ 4 cited

SRPCN: Structure Retrieval based Point Completion Network

Kaiyi Zhang, Ximing Yang, Yuan Wu +1

Given partial objects and some complete ones as references, point cloud completion aims to recover authentic shapes. However, existing methods pay little attention to general shape…

cs.CV2021

Attention-based Transformation from Latent Features to Point Clouds

Kaiyi Zhang, Ximing Yang, Yuan Wu +1

In point cloud generation and completion, previous methods for transforming latent features to point clouds are generally based on fully connected layers (FC-based) or folding oper…

cs.CV2021

Generate Point Clouds with Multiscale Details from Graph-Represented Structures

Ximing Yang, Zhibo Zhang, Zhengfu He +1

As details are missing in most representations of structures, the lack of controllability to more information is one of the major weaknesses in structure-based controllable point c…