Haocheng Tang — accepted AI-conference papers

2026

GauMVC: Generative Decoupled Gaussian Representation for Human-centric Multi-view Video Compression

Ruoke Yan, Mingjia Yang, Xinfeng Zhang, Haocheng Tang, Qian Yin, Zhipin Deng +3

CVPR 2026

Human-centric multi-view video has a clear semantic structure: a static background and dynamic human motion. We propose a generative compression framework that explicitly decouples these components. The background is modeled once with 3D Gaussian Splatting, while the human is represented by a person

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2026

Parallax to Align Them All: An OmniParallax Attention Mechanism for Distributed Multi-View Image Compression

Haotian Zhang, Feiyue Long, Yixin Yu, Jian Xue, Haocheng Tang, Tongda Xu +4

CVPR 2026

Multi-view image compression (MIC) aims to achieve high compression efficiency by exploiting inter-image correlations, playing a crucial role in 3D applications. As a subfield of MIC, distributed multi-view image compression (DMIC) offers performance comparable to MIC while eliminating the need for

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