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cs.CV2026

LoopMoEVR: Loop-Based Degradation-Aware Mixture-of-Experts for Unified UHD Video Restoration

Yucheng Xin, Runci Bai, Yongcong Wang +5

Recently, unified high-definition image restoration has attracted considerable attention; however, existing models tend to excessively increase their depth in pursuit of improved g…

cs.CV2026

LoopLUT: 3D Lookup Tables with Progressive Region Refinement for Real-Time 4K Image Enhancement

Yang Ye, Jiajun Ma, Chen Wu +5

Color enhancement of 4K images must meet a quality target under a tight compute budget. Three-dimensional lookup tables (3D LUTs) dominate real-time enhancement because they decide…

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

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

RPBA-Net: An Interpretable Residual Pyramid Bilateral Affine Network for RAW-Domain ISP Enhancement

Yucheng Xin, Wu Chen, Xiang Chen +7

To address module fragmentation, uninterpretable mappings, and deployment constraints in RAW-domain demosaicing, color correction, and detail enhancement, this paper proposes RPBA-…

cs.CV2026

6thGrid-Net: Unified Remote Sensing Image Dehazing Based on Color Restoration and Edge-Preserving

Runci Bai, Kui Jiang, Xiang Chen +4

Remote sensing images are frequently degraded by adverse weather conditions, particularly clouds and haze, which severely impair downstream applications. Existing restoration metho…

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…

eess.IV2026

UHD Low-Light Image Enhancement via Real-Time Enhancement Methods with Clifford Information Fusion

Xiaohan Wang, Chen Wu, Dawei Zhao +8

Considering efficiency, ultra-high-definition (UHD) low-light image restoration is extremely challenging. Existing methods based on Transformer architectures or high-dimensional co…

cs.CV2026

Unifying VLM-Guided Flow Matching and Spectral Anomaly Detection for Interpretable Veterinary Diagnosis

Pu Wang, Zhixuan Mao, Jialu Li +3

Automatic diagnosis of canine pneumothorax is challenged by data scarcity and the need for trustworthy models. To address this, we first introduce a public, pixel-level annotated d…

cs.CV2026

UHD Image Deblurring via Autoregressive Flow with Ill-conditioned Constraints

Yucheng Xin, Dawei Zhao, Xiang Chen +6

Ultra-high-definition (UHD) image deblurring poses significant challenges for UHD restoration methods, which must balance fine-grained detail recovery and practical inference effic…

cs.CV2026

Teacher-Guided Causal Interventions for Image Denoising: Orthogonal Content-Noise Disentanglement in Vision Transformers

Kuai Jiang, Zhaoyan Ding, Guijuan Zhang +2

Conventional image denoising models often inadvertently learn spurious correlations between environmental factors and noise patterns. Moreover, due to high-frequency ambiguity, the…

cs.CV2026

SSPFormer: Self-Supervised Pretrained Transformer for MRI Images

Jingkai Li, Xiaoze Tian, Yuhang Shen +4

The pre-trained transformer demonstrates remarkable generalization ability in natural image processing. However, directly transferring it to magnetic resonance images faces two key…