https://git5.cs.fau.de/folle/sr-cest
공식 코드Towards Super-Resolution CEST MRI for Visualization of Small Structures
Papers with Code 아카이브
SSIM
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/05kashyap/AutoEncoded_Image_Transfer
공식 코드Autoencoded Image Compression for Secure and Fast Transmission
https://github.com/16lemoing/waldo
공식 코드WALDO: Future Video Synthesis using Object Layer Decomposition and Parametric Flow Prediction
https://github.com/505030475/ExtremeLowLight
공식 코드Learning an Adaptive Model for Extreme Low-light Raw Image Processing
https://github.com/AAleka/Cycle-CBAM-and-CBAM-UNet/tree/main/UNet
공식 코드Retinal Image Restoration and Vessel Segmentation using Modified Cycle-CBAM and CBAM-UNet
https://github.com/AIRLabIISc/OceanLens
공식 코드https://github.com/Ali-Meh619/FKAN
공식 코드Implicit Neural Representations with Fourier Kolmogorov-Arnold Networks
https://github.com/BianChang/HEMIT-DATASET
공식 코드HEMIT: H&E to Multiplex-immunohistochemistry Image Translation with Dual-Branch Pix2pix Generator
https://github.com/BoPang1996/Deep-RNN-Framework
공식 코드https://github.com/Booooooooooo/CSD
공식 코드Towards Compact Single Image Super-Resolution via Contrastive Self-distillation
https://github.com/CSU-BME/pathology_MSR
공식 코드Multi-scale super-resolution generation of low-resolution scanned pathological images
https://github.com/ChengzeYe/Defrise-and-Clack-reconstruction
공식 코드DRACO: Differentiable Reconstruction for Arbitrary CBCT Orbits
https://github.com/ChenyangLEI/flash-reflection-removal
공식 코드Robust Reflection Removal with Reflection-free Flash-only Cues
https://github.com/DS3Lab/odlc
공식 코드https://github.com/DVLP-CMATERJU/RectiNet
공식 코드A Gated and Bifurcated Stacked U-Net Module for Document Image Dewarping
https://github.com/Fabio-Gil-Z/IRUNet
공식 코드Blind microscopy image denoising with a deep residual and multiscale encoder/decoder network
https://github.com/Felixduelmer/phocus
공식 코드PHOCUS: Physics-Based Deconvolution for Ultrasound Resolution Enhancement
https://github.com/GabrieleLozupone/LDAE
공식 코드https://github.com/GiuliaDAngelo/Speckegomotion
공식 코드Wandering around: A bioinspired approach to visual attention through object motion sensitivity
https://github.com/GuoLusjtu/DVC
공식 코드https://github.com/HiLab-git/GLFC
공식 코드https://github.com/Holmes-Alan/RefVAE
공식 코드Variational AutoEncoder for Reference based Image Super-Resolution
https://github.com/HrishikeshVish/AdaFNIO
공식 코드AdaFNIO: Adaptive Fourier Neural Interpolation Operator for video frame interpolation
https://github.com/HuiZeng/Image-Adaptive-3DLUT
공식 코드Learning Image-adaptive 3D Lookup Tables for High Performance Photo Enhancement in Real-time
https://github.com/IMPLabUniPr/swin2-mose
공식 코드Swin2-MoSE: A New Single Image Super-Resolution Model for Remote Sensing
https://github.com/Iman-yazdanpanah/contrastive-SSIM-SCGAN
공식 코드Improving SCGAN's Similarity Constraint and Learning a Better Disentangled Representation
https://github.com/InterDigitalInc/CompressAI
공식 코드CompressAI: a PyTorch library and evaluation platform for end-to-end compression research
https://github.com/Jahid12012021/Adaptive-Weight-Modified-Riesz-Mean-Filter-For-High-Density-Salt-and-Pepper-Noise-Removal
공식 코드Adaptive Weight Modified Riesz Mean Filter For High-Density Salt and Pepper Noise Removal
https://github.com/JasonZHM/CAE-ADMM
공식 코드CAE-ADMM: Implicit Bitrate Optimization via ADMM-based Pruning in Compressive Autoencoders
https://github.com/JasonZHM/CAEP
공식 코드CAE-ADMM: Implicit Bitrate Optimization via ADMM-based Pruning in Compressive Autoencoders
https://github.com/Jiamian-Wang/HSI_baseline
공식 코드A Simple and Efficient Reconstruction Backbone for Snapshot Compressive Imaging
https://github.com/JianpingLin/M-LVC_CVPR2020
공식 코드M-LVC: Multiple Frames Prediction for Learned Video Compression
https://github.com/JomaMinoza/Ocean-Floor-Mapping-with-Uncertainty-Aware-Deep-Learning
공식 코드Learning Enhanced Structural Representations with Block-Based Uncertainties for Ocean Floor Mapping
https://github.com/JooyoungLeeETRI/CA_Entropy_Model
공식 코드Context-adaptive Entropy Model for End-to-end Optimized Image Compression
https://github.com/KUIS-AI-Tekalp-Research-Group/video-compression
공식 코드End-to-End Rate-Distortion Optimized Learned Hierarchical Bi-Directional Video Compression
https://github.com/KishanKancharagunta/CSGAN
공식 코드CSGAN: Cyclic-Synthesized Generative Adversarial Networks for Image-to-Image Transformation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.