most citedLinear Attention Modeling for Learned Image Compression

1 citations · 1 across the 6 of their papers we have counts for

collaborators

7 papers

cs.MM2026

A Low-Latency Interactive System for Real-Time Video Understanding Based on VLMs

Punan Dai, Jun Xu, Bingcong Lu +4

Vision-language models are extending video understanding from offline clip analysis to continuous interactive streaming, but most research still emphasizes model capability rather…

cs.CV2026

Decoupled Self-Forcing Distillation for Streaming Talking Head Generation

Yanru An, Ruiyan Wang, Wenwu Wei +7

Streaming talking-head generation produces each frame as its driving audio arrives, yet fidelity and efficiency have so far pulled in opposite directions: end-to-end methods condit…

cs.CV2026

Visual Token Codec: Unleashing Spatial Redundancy for ViT Feature Coding

Donghui Feng, Fengxi Zhang, Changsheng Gao +6

Distributed deployment of large vision foundation models often partitions a ViT backbone and exchanges intermediate token features between computing nodes, making efficient feature…

cs.AI2026

MeetBench-XL: Calibrated Multi-Dimensional Evaluation and Learned Dual-Policy Agents for Real-Time Meetings

Yuelin Hu, Jun Xu, Bingcong Lu +4

Enterprise meeting environments require AI assistants that handle diverse operational tasks, from rapid fact checking during live discussions to cross meeting analysis for strategi…

cs.CV2026

Lightweight High-Fidelity Low-Bitrate Talking Face Compression for 3D Video Conference

Jianglong Li, Jun Xu, Bingcong Lu +4

The demand for immersive and interactive communication has driven advancements in 3D video conferencing, yet achieving high-fidelity 3D talking face representation at low bitrates…

cs.CV2025

Content-Aware Mamba for Learned Image Compression

Yunuo Chen, Zezheng Lyu, Bing He +6

Recent learned image compression (LIC) leverages Mamba-style state-space models (SSMs) for global receptive fields with linear complexity. However, the standard Mamba adopts conten…

cs.CV2025★ 1 cited

Linear Attention Modeling for Learned Image Compression

Donghui Feng, Zhengxue Cheng, Shen Wang +4

Recent years, learned image compression has made tremendous progress to achieve impressive coding efficiency. Its coding gain mainly comes from non-linear neural network-based tran…