https://github.com/valfride/lpr-rsr
공식 코드Combining Attention Module and Pixel Shuffle for License Plate Super-Resolution
Papers with Code 아카이브
Image Super-Resolution
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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/valfride/lpr-rsr-ext
공식 코드Super-Resolution of License Plate Images Using Attention Modules and Sub-Pixel Convolution Layers
https://github.com/vdeborto/cdsb
공식 코드https://github.com/vibss2397/Real-Time-Super-Resolution-For-Microscopic-Images-Using-GAN
공식 코드Attaining Real-Time Super-Resolution for Microscopic Images Using GAN
https://github.com/victor-nasc/Vehicle-Counting
공식 코드https://github.com/vios-s/CMRxRECON_Challenge_EDIPO
공식 코드Cine cardiac MRI reconstruction using a convolutional recurrent network with refinement
https://github.com/vipgugr/CADUF
공식 코드Fast and Robust Cascade Model for Multiple Degradation Single Image Super-Resolution
https://github.com/visinf/n3net
공식 코드https://github.com/visioniclab/swinfusr
공식 코드SwinFuSR: an image fusion-inspired model for RGB-guided thermal image super-resolution
https://github.com/vsantjr/dl_blindsr
공식 코드https://github.com/vsantjr/ideeps
공식 코드https://github.com/waleedgondal/Texture-based-Super-Resolution-Network
공식 코드The Unreasonable Effectiveness of Texture Transfer for Single Image Super-resolution
https://github.com/wdmwhh/MRefSR
공식 코드LMR: A Large-Scale Multi-Reference Dataset for Reference-based Super-Resolution
https://github.com/weiyithu/FGR
공식 코드FGR: Frustum-Aware Geometric Reasoning for Weakly Supervised 3D Vehicle Detection
https://github.com/weizhou-geek/SFSN
공식 코드Image Super-Resolution Quality Assessment: Structural Fidelity Versus Statistical Naturalness
https://github.com/weizhou-geek/srif
공식 코드Quality Assessment of Image Super-Resolution: Balancing Deterministic and Statistical Fidelity
https://github.com/wenyu1009/rtsrn
공식 코드Pixel Adapter: A Graph-Based Post-Processing Approach for Scene Text Image Super-Resolution
https://github.com/wgcban/DIP-HyperKite
공식 코드Hyperspectral Pansharpening Based on Improved Deep Image Prior and Residual Reconstruction
https://github.com/worldstrat/worldstrat
공식 코드https://github.com/wustl-cig/mbdl_pruning
공식 코드Efficient Model-Based Deep Learning via Network Pruning and Fine-Tuning
https://github.com/wut-ai/hypersound
공식 코드Hypernetworks build Implicit Neural Representations of Sounds
https://github.com/wwangcece/sgdm
공식 코드https://github.com/wxxxxxxh/A2F-SR
공식 코드Lightweight Single-Image Super-Resolution Network with Attentive Auxiliary Feature Learning
https://github.com/wyf0912/sinsr
공식 코드SinSR: Diffusion-Based Image Super-Resolution in a Single Step
https://github.com/wyhuai/ddnm
공식 코드Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model
https://github.com/wyhuai/rnd
공식 코드GAN Prior based Null-Space Learning for Consistent Super-Resolution
https://github.com/wzhshi/MSSRNet
공식 코드https://github.com/xahidbuffon/srdrm
공식 코드Underwater Image Super-Resolution using Deep Residual Multipliers
https://github.com/xiaom233/bsrn
공식 코드Blueprint Separable Residual Network for Efficient Image Super-Resolution
https://github.com/xiezw5/Component-Divide-and-Conquer-for-Real-World-Image-Super-Resolution
공식 코드Component Divide-and-Conquer for Real-World Image Super-Resolution
https://github.com/xinDW/RFGANM
공식 코드High-throughput, high-resolution registration-free generated adversarial network microscopy
https://github.com/xindongzhang/elan
공식 코드Efficient Long-Range Attention Network for Image Super-resolution
https://github.com/xinntao/ESRGAN
공식 코드ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/xinntao/SFTGAN
공식 코드Recovering Realistic Texture in Image Super-resolution by Deep Spatial Feature Transform
https://github.com/xiuheng-wang/Deep_gradient_HSI_superresolution
공식 코드Hyperspectral Image Super-resolution with Deep Priors and Degradation Model Inversion
https://github.com/xiuheng-wang/Sylvester_TSFN_MDC_HSI_superresolution
공식 코드Hyperspectral Image Super-Resolution via Deep Prior Regularization with Parameter Estimation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.