https://github.com/Sebbyraft/Spatio-Temporal_SAR-Optical_Data_Fusion_for_Cloud_Removal
공식 코드Spatio-Temporal SAR-Optical Data Fusion for Cloud Removal via a Deep Hierarchical Model
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Image Restoration is a family of inverse problems for obtaining a high quality image from a corrupted input image. Corruption may occur due to the image-capture process (e.g., noise, lens blur), post-processing (e.g., JPEG compression), or photography in non-ideal conditions (e.g., haze, motion blur).
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Spatio-Temporal SAR-Optical Data Fusion for Cloud Removal via a Deep Hierarchical Model
Extremely Low-light Image Enhancement with Scene Text Restoration
SAPNet: Segmentation-Aware Progressive Network for Perceptual Contrastive Deraining
Restorer: Removing Multi-Degradation with All-Axis Attention and Prompt Guidance
Difflare: Removing Image Lens Flare with Latent Diffusion Model
Prompt-based Ingredient-Oriented All-in-One Image Restoration
A Mountain-Shaped Single-Stage Network for Accurate Image Restoration
Exploring Richer and More Accurate Information via Frequency Selection for Image Restoration
Learning a Single Model with a Wide Range of Quality Factors for JPEG Image Artifacts Removal
QC-StyleGAN -- Quality Controllable Image Generation and Manipulation
Denoising Prior Driven Deep Neural Network for Image Restoration
Learning Invariant Representation for Unsupervised Image Restoration
MaIR: A Locality- and Continuity-Preserving Mamba for Image Restoration
A Dynamic Kernel Prior Model for Unsupervised Blind Image Super-Resolution
Exploiting Deep Generative Prior for Versatile Image Restoration and Manipulation
Infrared Image Deturbulence Restoration Using Degradation Parameter-Assisted Wide & Deep Learning
Transitional Learning: Exploring the Transition States of Degradation for Blind Super-resolution
NAS-DIP: Learning Deep Image Prior with Neural Architecture Search
Learning Efficient and Effective Trajectories for Differential Equation-based Image Restoration
Uformer: A General U-Shaped Transformer for Image Restoration
Joint Learning Content and Degradation Aware Feature for Blind Super-Resolution
Perceptual-Distortion Balanced Image Super-Resolution is a Multi-Objective Optimization Problem
Retinal Image Restoration and Vessel Segmentation using Modified Cycle-CBAM and CBAM-UNet
Retinal Image Restoration using Transformer and Cycle-Consistent Generative Adversarial Network
Image Super-Resolution as a Defense Against Adversarial Attacks
Accelerating Multiframe Blind Deconvolution via Deep Learning
Real-time 6K Image Rescaling with Rate-distortion Optimization
Deep Hyperspectral Prior: Denoising, Inpainting, Super-Resolution
LVRNet: Lightweight Image Restoration for Aerial Images under Low Visibility
A-ESRGAN: Training Real-World Blind Super-Resolution with Attention U-Net Discriminators
PixWizard: Versatile Image-to-Image Visual Assistant with Open-Language Instructions
Gradient-Guided Parameter Mask for Multi-Scenario Image Restoration Under Adverse Weather
Replacing Mobile Camera ISP with a Single Deep Learning Model
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.