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20242026
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cs.CV2025

TeSO: Representing and Compressing 3D Point Cloud Scenes with Textured Surfel Octree

Yueyu Hu, Ran Gong, Tingyu Fan +1

3D visual content streaming is a key technology for emerging 3D telepresence and AR/VR applications. One fundamental element underlying the technology is a versatile 3D representat…

cs.CV2025

U-Motion: Learned Point Cloud Video Compression with U-Structured Temporal Context Generation

Tingyu Fan, Yueyu Hu, Ran Gong +1

Point cloud video (PCV) is a versatile 3D representation of dynamic scenes with emerging applications. This paper introduces U-Motion, a learning-based compression scheme for both…

cs.CV2024

Spatial Visibility and Temporal Dynamics: Revolutionizing Field of View Prediction in Adaptive Point Cloud Video Streaming

Chen Li, Tongyu Zong, Yueyu Hu +2

Field-of-View (FoV) adaptive streaming significantly reduces bandwidth requirement of immersive point cloud video (PCV) by only transmitting visible points in a viewer's FoV. The t…

cs.CV2024

Bits-to-Photon: End-to-End Learned Scalable Point Cloud Compression for Direct Rendering

Yueyu Hu, Ran Gong, Yao Wang

Point cloud is a promising 3D representation for volumetric streaming in emerging AR/VR applications. Despite recent advances in point cloud compression, decoding and rendering hig…

cs.CV2024

Low Latency Point Cloud Rendering with Learned Splatting

Yueyu Hu, Ran Gong, Qi Sun +1

Point cloud is a critical 3D representation with many emerging applications. Because of the point sparsity and irregularity, high-quality rendering of point clouds is challenging a…

cs.CV2024

Standard compliant video coding using low complexity, switchable neural wrappers

Yueyu Hu, Chenhao Zhang, Onur G. Guleryuz +2

The proliferation of high resolution videos posts great storage and bandwidth pressure on cloud video services, driving the development of next-generation video codecs. Despite gre…