7 papers
ResPCC: A Loss-Resilient Neural Point Cloud Codec over Lossy Networks
Xueqin Niu, Mufan Liu, Yifan Wang +3
Point cloud compression (PCC) is critical for efficient storage and transmission of 3D data. While recent learning-based PCC methods achieve good rate-distortion (R-D) performance,…
Progressively Deformable 2D Gaussian Splatting for Video Representation at Arbitrary Resolutions
Mufan Liu, Qi Yang, Miaoran Zhao +4
Implicit neural representations (INRs) enable fast video compression and effective video processing, but a single model rarely offers scalable decoding across rates and resolutions…
Rasterizing Wireless Radiance Field via Deformable 2D Gaussian Splatting
Mufan Liu, Cixiao Zhang, Qi Yang +6
Modeling the wireless radiance field (WRF) is fundamental to modern communication systems, enabling key tasks such as localization, sensing, and channel estimation. Traditional app…
Light4GS: Lightweight Compact 4D Gaussian Splatting Generation via Context Model
Mufan Liu, Qi Yang, He Huang +4
3D Gaussian Splatting (3DGS) has emerged as an efficient and high-fidelity paradigm for novel view synthesis. To adapt 3DGS for dynamic content, deformable 3DGS incorporates tempor…
ADC-GS: Anchor-Driven Deformable and Compressed Gaussian Splatting for Dynamic Scene Reconstruction
He Huang, Qi Yang, Mufan Liu +2
Existing 4D Gaussian Splatting methods rely on per-Gaussian deformation from a canonical space to target frames, which overlooks redundancy among adjacent Gaussian primitives and r…
Video Streaming with Kairos: An MPC-Based ABR with Streaming-Aware Throughput Prediction
Ziyu Zhong, Mufan Liu, Le Yang +3
In this paper, we present Kairos, a model predictive control (MPC)-based adaptive bitrate (ABR) scheme that integrates streaming-aware throughput predictions to enhance video strea…