collaborators

5 papers

cs.CV2026

Loop-Mamba: A Loop Mamba with Degradation-Aware and Shared Memory for Old Photo Restoration

Runci Bai, Yucheng Xin, Pu Wang +8

Old photographs often suffer from multiple coupled degradations, including scratches, cracks, fading, blur, noise, and missing regions, severely degrading both visual quality and s…

cs.CV2026

MoCRA: Mixture of Compositional Rank-1 Atoms for 4K All-in-One Video Restoration

Yongcong Wang, Pu Wang, Hingchin Chen +8

Real-world video arrives hazy, rainy, dark, or noisy, and a deployable restorer faces three demands at once: no degradation label, native 4K output, and stability in playback. Exis…

cs.CV2026

LiBrA-Net: Lie-Algebraic Bilateral Affine Fields for Real-Time 4K Video Dehazing

Yongcong Wang, Chengchao Shen, Guangwei Gao +5

Currently, there is a gap in the field of ultra-high-definition (UHD) video dehazing due to the lack of a benchmark for evaluation. Furthermore, existing video dehazing methods can…

cs.CV2026

UHD-GPGNet: UHD Video Denoising via Gaussian-Process-Guided Local Spatio-Temporal Modeling

Weiyuan He, Chen Wu, Pengwen Dai +6

Ultra-high-definition (UHD) video denoising requires simultaneously suppressing complex spatio-temporal degradations, preserving fine textures and chromatic stability, and maintain…

cs.CV2025

UHD Image Dehazing via anDehazeFormer with Atmospheric-aware KV Cache

Pu Wang, Pengwen Dai, Chen Wu +5

In this paper, we propose an efficient visual transformer framework for ultra-high-definition (UHD) image dehazing that addresses the key challenges of slow training speed and high…