https://github.com/WeishengDong/DPDNN_PyTorch
공식 코드Denoising Prior Driven Deep Neural Network for Image Restoration
Papers with Code 아카이브
Super-Resolution
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 보존된 평가 기록
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Super-Resolution is a task in computer vision that involves increasing the resolution of an image or video by generating missing high-frequency details from low-resolution input. The goal is to produce an output image with a higher resolution than the input image, while preserving the original content and structure.
<span style="color:grey; opacity: 0.6">( Credit: MemNet )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Wenri/DTSN
공식 코드Image Super-Resolution via Deterministic-Stochastic Synthesis and Local Statistical Rectification
https://github.com/XLearning-SCU/2025-CVPR-MaIR
공식 코드MaIR: A Locality- and Continuity-Preserving Mamba for Image Restoration
https://github.com/XY-boy/FreMamba
공식 코드Frequency-Assisted Mamba for Remote Sensing Image Super-Resolution
https://github.com/XYLGroup/DKP
공식 코드A Dynamic Kernel Prior Model for Unsupervised Blind Image Super-Resolution
https://github.com/XiangFeng66/SR-GS
공식 코드https://github.com/Xiangtaokong/ClassSR
공식 코드ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic
https://github.com/XieQi2015/F-Conv
공식 코드Fourier Series Expansion Based Filter Parametrization for Equivariant Convolutions
https://github.com/XinyiYing/D3Dnet
공식 코드https://github.com/XuechenZhang123/LCSC
공식 코드LCSCNet: Linear Compressing Based Skip-Connecting Network for Image Super-Resolution
https://github.com/YangLing0818/Diffusion-Models-Papers-Survey-Taxonomy
공식 코드Diffusion Models: A Comprehensive Survey of Methods and Applications
https://github.com/YingqianWang/LF-InterNet
공식 코드Spatial-Angular Interaction for Light Field Image Super-Resolution
https://github.com/YingqianWang/NUDT-Dataset
공식 코드Light Field Image Super-Resolution Using Deformable Convolution
https://github.com/YingqianWang/iPASSR
공식 코드Symmetric Parallax Attention for Stereo Image Super-Resolution
https://github.com/YooJiHyeong/SinIR
공식 코드SinIR: Efficient General Image Manipulation with Single Image Reconstruction
https://github.com/YuGuangWang/FGT
공식 코드Decimated Framelet System on Graphs and Fast G-Framelet Transforms
https://github.com/YuYin1/JASRNet
공식 코드https://github.com/YuanfeiHuang/DeFiAN
공식 코드Interpretable Detail-Fidelity Attention Network for Single Image Super-Resolution
https://github.com/YuanfeiHuang/IKM
공식 코드Image-specific Convolutional Kernel Modulation for Single Image Super-resolution
https://github.com/YuanfeiHuang/TLSR
공식 코드Transitional Learning: Exploring the Transition States of Degradation for Blind Super-resolution
https://github.com/YuvalBahat/Explorable-Super-Resolution/tree/gh-pages/codes
공식 코드https://github.com/YuzheZhang-1999/DiffTSR
공식 코드https://github.com/ZZUTK/SRNTT
공식 코드https://github.com/Zeqiang-Lai/HSI-RefSR
공식 코드Hyperspectral Image Super Resolution with Real Unaligned RGB Guidance
https://github.com/Zheng222/IDN-Caffe
공식 코드Fast and Accurate Single Image Super-Resolution via Information Distillation Network
https://github.com/Zheng222/IMDN
공식 코드Lightweight Image Super-Resolution with Information Multi-distillation Network
https://github.com/Zheng222/PPON
공식 코드Progressive Perception-Oriented Network for Single Image Super-Resolution
https://github.com/ZhengyuLiang24/LFT
공식 코드https://github.com/ZhouYiiFeng/CDSR
공식 코드Joint Learning Content and Degradation Aware Feature for Blind Super-Resolution
https://github.com/ZhuKeven/MOBOSR
공식 코드Perceptual-Distortion Balanced Image Super-Resolution is a Multi-Objective Optimization Problem
https://github.com/ZhuangLab/storm-analysis
공식 코드Teaching deep neural networks to localize single molecules for super-resolution microscopy
https://github.com/aamir-mustafa/Transformation-CR
공식 코드Transformation Consistency Regularization- A Semi-Supervised Paradigm for Image-to-Image Translation
https://github.com/aamir-mustafa/super-resolution-adversarial-defense
공식 코드Image Super-Resolution as a Defense Against Adversarial Attacks
https://github.com/aangelopoulos/im2im-uq
공식 코드https://github.com/aaravamudan2014/SIDDIS
공식 코드Data-driven Super-Resolution of Flood Inundation Maps using Synthetic Simulations
https://github.com/abnervictor/hyperthumbnail
공식 코드Real-time 6K Image Rescaling with Rate-distortion Optimization
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.