activity
20242026
collaborators

10 papers

eess.IV2026

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,…

cs.CV2025

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…

cs.CV2025

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…

cs.NI2025

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…

cs.CV2025

SED-MVS: Segmentation-Driven and Edge-Aligned Deformation Multi-View Stereo with Depth Restoration and Occlusion Constraint

Zhenlong Yuan, Zhidong Yang, Yujun Cai +6

Recently, patch-deformation methods have exhibited significant effectiveness in multi-view stereo owing to the deformable and expandable patches in reconstructing textureless areas…

cs.CV2025

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…

cs.CV2025

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…

cs.MM2024

Deep joint source-channel coding for wireless point cloud transmission

Cixiao Zhang, Mufan Liu, Wenjie Huang +3

The growing demand for high-quality point cloud transmission over wireless networks presents significant challenges, primarily due to the large data sizes and the need for efficien…

cs.MM2024

StreamOptix: A Cross-layer Adaptive Video Delivery Scheme

Mufan Liu, Le Yang, Yifan Wang +3

This paper presents a cross-layer video delivery scheme, StreamOptix, and proposes a joint optimization algorithm for video delivery that leverages the characteristics of the physi…

eess.IV2024

EVAN: Evolutional Video Streaming Adaptation via Neural Representation

Mufan Liu, Le Yang, Yiling Xu +2

Adaptive bitrate (ABR) using conventional codecs cannot further modify the bitrate once a decision has been made, exhibiting limited adaptation capability. This may result in eithe…