GeoQE: Enhancing Quality of Experience in Point Cloud Streaming

摘要

Point cloud compression (PCC) is indispensable for the upcoming holographic communication, enabling efficient transmission and real-time interaction with high-fidelity 3D data. As a mature international PCC standard, MPEG G-PCC holds promise for widespread applications due to its support for various point cloud types and ease of implementation. However, the geometry compression performance of G-PCC is limited, which severely impacts the user quality of experience (QoE). To address this, we propose GeoQE, an enhancement model that seamlessly integrates with the G-PCC decoder to mitigate compression artifacts and improve QoE. GeoQE introduces two key techniques: (1) a quantizer-guided expansion operation that adaptively handles distortions at varying levels, and (2) a spatiotemporal mechanism that leverages correlations within the current frame and across adjacent frames, allowing effective enhancement even with a lightweight network. Experiments show that GeoQE delivers state-of-the-art performance on both dense (e.g., VR/AR) and sparse (e.g., LiDAR for autonomous driving) point clouds. Operating at around 4 fps on a 3090Ti GPU with a compact 1.6 MB model, it achieves much lower computational complexity than existing methods, which is attractive for practical applications.