Papers with Code 아카이브
Color Image Denoising
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Hierarchical Information Flow for Generalized Efficient Image Restoration
Instruct-IPT: All-in-One Image Processing Transformer via Weight Modulation
Residual-Conditioned Optimal Transport: Towards Structure-Preserving Unpaired and Paired Image Restoration
Color Image Denoising Using The Green Channel Prior
LYT-NET: Lightweight YUV Transformer-based Network for Low-light Image Enhancement
A Theoretically Guaranteed Quaternion Weighted Schatten p-norm Minimization Method for Color Image Restoration
A Novel Truncated Norm Regularization Method for Multi-channel Color Image Denoising
Stimulating Diffusion Model for Image Denoising via Adaptive Embedding and Ensembling
A Dive into SAM Prior in Image Restoration
SwinIA: Self-Supervised Blind-Spot Image Denoising without Convolutions
KBNet: Kernel Basis Network for Image Restoration
Multi-channel Nuclear Norm Minus Frobenius Norm Minimization for Color Image Denoising
Polarized Color Image Denoising using Pocoformer
0/1 Deep Neural Networks via Block Coordinate Descent
Hypernetwork-Based Adaptive Image Restoration
Adversarial Distortion Learning for Medical Image Denoising
Improving Image Restoration by Revisiting Global Information Aggregation
Restormer: Efficient Transformer for High-Resolution Image Restoration
SwinIR: Image Restoration Using Swin Transformer
Patch Craft: Video Denoising by Deep Modeling and Patch Matching
Quaternion higher-order singular value decomposition and its applications in color image processing
Color Image Restoration Exploiting Inter-channel Correlation with a 3-stage CNN
Pre-Trained Image Processing Transformer
Rank-One Network: An Effective Framework for Image Restoration
Frequency-Weighted Robust Tensor Principal Component Analysis
KRNET: Image Denoising with Kernel Regulation Network
Rethinking the CSC Model for Natural Images
Pyramid Real Image Denoising Network
Blind Universal Bayesian Image Denoising with Gaussian Noise Level Learning
GRDN:Grouped Residual Dense Network for Real Image Denoising and GAN-based Real-world Noise Modeling
ViDeNN: Deep Blind Video Denoising
Modulating Image Restoration with Continual Levels via Adaptive Feature Modification Layers
Real Image Denoising with Feature Attention
Noise2Self: Blind Denoising by Self-Supervision
Residual Dense Network for Image Restoration
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.