2 citations · 3 across the 9 of their papers we have counts for
11 papers · 1 filter
Bidirectional Cross-frequency Domain Interaction Network for UHD Low-Light Image Enhancement
Bo Fu, Hai Chi, Liyan Wang +5
Existing Ultra-High-Definition (UHD) low-light image enhancement (LLIE) methods typically rely on either spatial- or frequency-domain modeling, or independently process different f…
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…
Ultra-High-Definition Restoration Transformers with Correlation Matching Transformation
Cong Wang, Liyan Wang, Jinshan Pan +4
We propose UHDformer++, a general Transformer-based framework to solve numerous Ultra-High-Definition (UHD) image restoration tasks. UHDformer++ operates across coordinated lea…
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…
Neural Discrimination-Prompted Transformers for Efficient UHD Image Restoration and Enhancement
Cong Wang, Jinshan Pan, Liyan Wang +2
We propose a simple yet effective UHDPromer, a neural discrimination-prompted Transformer, for Ultra-High-Definition (UHD) image restoration and enhancement. Our UHDPromer is inspi…
Blind Deconvolution for Color Images Using Normalized Quaternion Kernels
Yuming Yang, Michael K. Ng, Zhigang Jia +1
In this work, we address the challenging problem of blind deconvolution for color images. Existing methods often convert color images to grayscale or process each color channel sep…
Intra and Inter Parser-Prompted Transformers for Effective Image Restoration
Cong Wang, Jinshan Pan, Liyan Wang +1
We propose Intra and Inter Parser-Prompted Transformers (PPTformer) that explore useful features from visual foundation models for image restoration. Specifically, PPTformer contai…
Correlation Matching Transformation Transformers for UHD Image Restoration
Cong Wang, Jinshan Pan, Wei Wang +5
This paper proposes UHDformer, a general Transformer for Ultra-High-Definition (UHD) image restoration. UHDformer contains two learning spaces: (a) learning in high-resolution spac…
Ultra-High-Definition Image Restoration: New Benchmarks and A Dual Interaction Prior-Driven Solution
Liyan Wang, Cong Wang, Jinshan Pan +5
Ultra-High-Definition (UHD) image restoration has acquired remarkable attention due to its practical demand. In this paper, we construct UHD snow and rain benchmarks, named UHD-Sno…
How Powerful Potential of Attention on Image Restoration?
Cong Wang, Jinshan Pan, Yeying Jin +5
Transformers have demonstrated their effectiveness in image restoration tasks. Existing Transformer architectures typically comprise two essential components: multi-head self-atten…
SelfPromer: Self-Prompt Dehazing Transformers with Depth-Consistency
Cong Wang, Jinshan Pan, Wanyu Lin +2
This work presents an effective depth-consistency self-prompt Transformer for image dehazing. It is motivated by an observation that the estimated depths of an image with haze resi…