15 citations · 18 across the 20 of their papers we have counts for
21 papers · 1 filter
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
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.…
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…
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…
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…
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…