https://github.com/lms-07/lgteun
공식 코드Local-Global Transformer Enhanced Unfolding Network for Pan-sharpening
Papers with Code 아카이브
Image Super-Resolution
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- 평가표
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Image Super-Resolution is a machine learning task where the goal is to increase the resolution of an image, often by a factor of 4x or more, while maintaining its content and details as much as possible. The end result is a high-resolution version of the original image. This task can be used for various applications such as improving image quality, enhancing visual detail, and increasing the accuracy of computer vision algorithms.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/lonelyhope/dada
공식 코드Dual Adversarial Adaptation for Cross-Device Real-World Image Super-Resolution
https://github.com/lose4578/SAM-DiffSR
공식 코드SAM-DiffSR: Structure-Modulated Diffusion Model for Image Super-Resolution
https://github.com/lpj-github-io/MWCNNv2
공식 코드https://github.com/lpj0/MWCNN
공식 코드https://github.com/lpj0/bde
공식 코드https://github.com/luciennnnnnn/dualformer
공식 코드On the Effectiveness of Spectral Discriminators for Perceptual Quality Improvement
https://github.com/luigisigillo/shipinsight
공식 코드Ship in Sight: Diffusion Models for Ship-Image Super Resolution
https://github.com/luissen/esrt
공식 코드https://github.com/lukazso/kpbms-pvdn
공식 코드https://github.com/luohongming/CISR_PSI
공식 코드https://github.com/lusinlu/gradient_variance_loss
공식 코드Gradient Variance Loss for Structure-Enhanced Image Super-Resolution
https://github.com/lycexe/structsr
공식 코드StructSR: Refuse Spurious Details in Real-World Image Super-Resolution
https://github.com/majedelhelou/SFM
공식 코드Stochastic Frequency Masking to Improve Super-Resolution and Denoising Networks
https://github.com/makinyilmaz/dimosr
공식 코드https://github.com/mandalinadagi/wavelettention
공식 코드https://github.com/mandalinadagi/wgsr
공식 코드https://github.com/marcelowds/sr-sde
공식 코드Face Super-Resolution Using Stochastic Differential Equations
https://github.com/marijavella/hs-sr-tvtv
공식 코드Enhanced Hyperspectral Image Super-Resolution via RGB Fusion and TV-TV Minimization
https://github.com/marijavella/sr-tvtvsolver
공식 코드Single Image Super-Resolution via CNN Architectures and TV-TV Minimization
https://github.com/marijavella/sr-via-CNNs-and-tvtv
공식 코드Robust Single-Image Super-Resolution via CNNs and TV-TV Minimization
https://github.com/matciotola/z-pnn
공식 코드Pansharpening by convolutional neural networks in the full resolution framework
https://github.com/megvii-research/NAFNet
공식 코드https://github.com/megvii-research/d2c-sr
공식 코드D2C-SR: A Divergence to Convergence Approach for Real-World Image Super-Resolution
https://github.com/megvii-research/dcls-sr
공식 코드Deep Constrained Least Squares for Blind Image Super-Resolution
https://github.com/melaseddik/GCN
공식 코드Generative Collaborative Networks for Single Image Super-Resolution
https://github.com/mengxiangming/dmps
공식 코드Diffusion Model Based Posterior Sampling for Noisy Linear Inverse Problems
https://github.com/merlresearch/SteeredDiffusion
공식 코드Steered Diffusion: A Generalized Framework for Plug-and-Play Conditional Image Synthesis
https://github.com/mhamilton723/FeatUp
공식 코드FeatUp: A Model-Agnostic Framework for Features at Any Resolution
https://github.com/ming053l/drct
공식 코드DRCT: Saving Image Super-resolution away from Information Bottleneck
https://github.com/minghanz/trafcam_3d
공식 코드Monocular 3D Vehicle Detection Using Uncalibrated Traffic Cameras through Homography
https://github.com/miracle-center/ctspine1k
공식 코드CTSpine1K: A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomography
https://github.com/mirthai/fast-ddpm
공식 코드Fast-DDPM: Fast Denoising Diffusion Probabilistic Models for Medical Image-to-Image Generation
https://github.com/mirthai/gdm-ve
공식 코드Geodesic Diffusion Models for Medical Image-to-Image Generation
https://github.com/mjq11302010044/TPGSR
공식 코드https://github.com/mjq11302010044/real-ce
공식 코드A Benchmark for Chinese-English Scene Text Image Super-resolution
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.