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20242026
most citedU-shaped Vision Mamba for Single Image Dehazing

15 citations · 18 across the 20 of their papers we have counts for

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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

Accurate Motion Estimation with Bézier Control Point for Efficient Frame Interpolation

Shuhao Han, Chenyang Wu, Chun-Le Guo +4

In frame interpolation tasks, motion ambiguity in the training set causes models to generate blurry intermediate frames. Moreover, the assumption of uniform motion between frames d…

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

FlowPainter: Inpainting Optical Flow via Confidence-Guided Completion

Yuang Meng, Chenyang Wu, Xianshun Liu +7

Existing optical flow methods broadly follow two paradigms: iterative optimization and diffusion-based estimation. Iterative methods, exemplified by RAFT, achieve high accuracy thr…

cs.CV2025

VTinker: Guided Flow Upsampling and Texture Mapping for High-Resolution Video Frame Interpolation

Chenyang Wu, Jiayi Fu, Chun-Le Guo +2

Due to large pixel movement and high computational cost, estimating the motion of high-resolution frames is challenging. Thus, most flow-based Video Frame Interpolation (VFI) metho…

cs.CV2025

FlowLUT: Efficient Image Enhancement via Differentiable LUTs and Iterative Flow Matching

Liubing Hu, Chen Wu, Anrui Wang +3

Deep learning-based image enhancement methods face a fundamental trade-off between computational efficiency and representational capacity. For example, although a conventional thre…

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…

cs.CV2025

Distribution-aware Dataset Distillation for Efficient Image Restoration

Zhuoran Zheng, Xin Su, Chen Wu +1

With the exponential increase in image data, training an image restoration model is laborious. Dataset distillation is a potential solution to this problem, yet current distillatio…

cs.CV2025

AdaQual-Diff: Diffusion-Based Image Restoration via Adaptive Quality Prompting

Xin Su, Chen Wu, Yu Zhang +2

Restoring images afflicted by complex real-world degradations remains challenging, as conventional methods often fail to adapt to the unique mixture and severity of artifacts prese…

cs.CV2025

UniFlowRestore: A General Video Restoration Framework via Flow Matching and Prompt Guidance

Shuning Sun, Yu Zhang, Chen Wu +4

Video imaging is often affected by complex degradations such as blur, noise, and compression artifacts. Traditional restoration methods follow a "single-task single-model" paradigm…

cs.CV2025

Bridge the Gap between SNN and ANN for Image Restoration

Xin Su, Chen Wu, Zhuoran Zheng

Models of dense prediction based on traditional Artificial Neural Networks (ANNs) require a lot of energy, especially for image restoration tasks. Currently, neural networks based…

cs.CV2024

TSFormer: A Robust Framework for Efficient UHD Image Restoration

Xin Su, Chen Wu, Zhuoran Zheng

Ultra-high-definition (UHD) image restoration is vital for applications demanding exceptional visual fidelity, yet existing methods often face a trade-off between restoration quali…

cs.CV2024

Dropout the High-rate Downsampling: A Novel Design Paradigm for UHD Image Restoration

Chen Wu, Ling Wang, Long Peng +2

With the popularization of high-end mobile devices, Ultra-high-definition (UHD) images have become ubiquitous in our lives. The restoration of UHD images is a highly challenging pr…

cs.CV2024

Multi-Scale Representation Learning for Image Restoration with State-Space Model

Yuhong He, Long Peng, Qiaosi Yi +2

Image restoration endeavors to reconstruct a high-quality, detail-rich image from a degraded counterpart, which is a pivotal process in photography and various computer vision syst…

cs.CV2024★ 1 cited

Review Learning: Advancing All-in-One Ultra-High-Definition Image Restoration Training Method

Xin Su, Zhuoran Zheng, Chen Wu

All-in-one image restoration tasks are becoming increasingly important, especially for ultra-high-definition (UHD) images. Existing all-in-one UHD image restoration methods usually…

cs.CV2024

Every Pixel Has its Moments: Ultra-High-Resolution Unpaired Image-to-Image Translation via Dense Normalization

Ming-Yang Ho, Che-Ming Wu, Min-Sheng Wu +1

Recent advancements in ultra-high-resolution unpaired image-to-image translation have aimed to mitigate the constraints imposed by limited GPU memory through patch-wise inference.…

cs.CV2024★ 1 cited

Towards Ultra-High-Definition Image Deraining: A Benchmark and An Efficient Method

Hongming Chen, Xiang Chen, Chen Wu +3

Despite significant progress has been made in image deraining, existing approaches are mostly carried out on low-resolution images. The effectiveness of these methods on high-resol…

cs.CV2024★ 15 cited

U-shaped Vision Mamba for Single Image Dehazing

Zhuoran Zheng, Chen Wu

Currently, Transformer is the most popular architecture for image dehazing, but due to its large computational complexity, its ability to handle long-range dependency is limited on…

cs.CV2024

Polyp-DAM: Polyp segmentation via depth anything model

Zhuoran Zheng, Chen Wu, Wei Wang +2

Recently, large models (Segment Anything model) came on the scene to provide a new baseline for polyp segmentation tasks. This demonstrates that large models with a sufficient imag…

cs.CV2024★ 1 cited

MixNet: Efficient Global Modeling for Ultra-High-Definition Image Restoration

Chen Wu, Zhuoran Zheng, Yuning Cui +1

Recent advancements in image restoration methods employing global modeling have shown promising results. However, these approaches often incur substantial memory requirements, part…