collaborators

5 papers

eess.IV2026

Inter-LPCM: Learning-based Inter-Frame Predictive Coding for LiDAR Point Cloud Compression

Chang Sun, Hui Yuan, Shiqi Jiang +3

Because LiDAR sensors acquire point clouds with a fixed angular resolution, the resulting data can be systematically parameterized and efficiently compressed in the spherical coord…

cs.CV2026

DUGAE: Unified Geometry and Attribute Enhancement via Spatiotemporal Correlations for G-PCC Compressed Dynamic Point Clouds

Pan Zhao, Hui Yuan, Chang Sun +3

Existing post-decoding quality enhancement methods for point clouds are designed for static data and typically process each frame independently. As a result, they cannot effectivel…

eess.IV2026

Point Cloud Feature Coding for Object Detection over an Error-Prone Cloud-Edge Collaborative System

Chongzhen Tian, Hui Yuan, Pan Zhao +3

Cloud-edge collaboration enhances machine perception by combining the strengths of edge and cloud computing. Edge devices capture raw data (e.g., 3D point clouds) and extract salie…

cs.CV2025

UGAE: Unified Geometry and Attribute Enhancement for G-PCC Compressed Point Clouds

Pan Zhao, Hui Yuan, Chongzhen Tian +3

Lossy compression of point clouds reduces storage and transmission costs; however, it inevitably leads to irreversible distortion in geometry structure and attribute information. T…

eess.IV2024

Feature Compression for Cloud-Edge Multimodal 3D Object Detection

Chongzhen Tian, Zhengxin Li, Hui Yuan +3

Machine vision systems, which can efficiently manage extensive visual perception tasks, are becoming increasingly popular in industrial production and daily life. Due to the challe…