Image-to-Image Translation
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Image-to-Image Translation is a task in computer vision and machine learning where the goal is to learn a mapping between an input image and an output image, such that the output image can be used to perform a specific task, such as style transfer, data augmentation, or image restoration.
<span style="color:grey; opacity: 0.6">( Image credit: Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Medabid1/I2I-LR
공식 코드https://github.com/MichalGeyer/plug-and-play
공식 코드Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translation
https://github.com/MoPl90/image_translation
공식 코드Image Translation for Medical Image Generation -- Ischemic Stroke Lesions
https://github.com/MohammadRSalmanpour/MRI-to-US-Translation_MICCAI
공식 코드https://github.com/Mukosame/AODA
공식 코드Adversarial Open Domain Adaptation for Sketch-to-Photo Synthesis
https://github.com/NVIDIA/pix2pixHD
공식 코드High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
https://github.com/NVlabs/FUNIT
공식 코드https://github.com/NVlabs/SPADE
공식 코드Semantic Image Synthesis with Spatially-Adaptive Normalization
https://github.com/NetEase-GameAI/SPatchGAN
공식 코드SPatchGAN: A Statistical Feature Based Discriminator for Unsupervised Image-to-Image Translation
https://github.com/Noodles-321/Registration
공식 코드Is Image-to-Image Translation the Panacea for Multimodal Image Registration? A Comparative Study
https://github.com/Nota-NetsPresso/BK-SDM
공식 코드BK-SDM: A Lightweight, Fast, and Cheap Version of Stable Diffusion
https://github.com/OcraM17/eXIE
공식 코드Explaining Image Enhancement Black-Box Methods through a Path Planning Based Algorithm
https://github.com/OmarSZamzam/PixelShuffler
공식 코드PixelShuffler: A Simple Image Translation Through Pixel Rearrangement
https://github.com/Onr/Council-GAN
공식 코드https://github.com/PITI-Synthesis/PITI
공식 코드https://github.com/Panagiotou/Procedural3DTerrain
공식 코드Procedural 3D Terrain Generation using Generative Adversarial Networks
https://github.com/Pangyk/SinoSynth
공식 코드SinoSynth: A Physics-based Domain Randomization Approach for Generalizable CBCT Image Enhancement
https://github.com/Paul92/cp_2020
공식 코드https://github.com/QiufanLin/ImageTranslation
공식 코드Galaxy Image Translation with Semi-supervised Noise-reconstructed Generative Adversarial Networks
https://github.com/RaoUmer/SRResCycGAN
공식 코드Deep Cyclic Generative Adversarial Residual Convolutional Networks for Real Image Super-Resolution
https://github.com/RogerZhangzz/CAG_UDA
공식 코드Category Anchor-Guided Unsupervised Domain Adaptation for Semantic Segmentation
https://github.com/RoyalVane/CLAN
공식 코드https://github.com/SURA23/Sinus-Surgery-Endoscopic-Image-Datasets
공식 코드LC-GAN: Image-to-image Translation Based on Generative Adversarial Network for Endoscopic Images
https://github.com/ShaniGam/RL-GAN
공식 코드Transfer Learning for Related Reinforcement Learning Tasks via Image-to-Image Translation
https://github.com/SharifAmit/Attention2Angio
공식 코드https://github.com/SharifAmit/VTGAN
공식 코드VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision Transformers
https://github.com/TAMU-VITA/GAN-Slimming
공식 코드GAN Slimming: All-in-One GAN Compression by A Unified Optimization Framework
https://github.com/TimeLighter/pytorch-sym-parameter
공식 코드Sym-parameterized Dynamic Inference for Mixed-Domain Image Translation
https://github.com/TingHLiao/ELDA
공식 코드ELDA: Using Edges to Have an Edge on Semantic Segmentation Based UDA
https://github.com/Trustworthy-Engineered-Autonomy-Lab/generalizable-image-repair
공식 코드Generalizable Image Repair for Robust Visual Autonomous Racing
https://github.com/TsaftarisCollaboratory/CSDisentanglement_Metrics_Library
공식 코드Measuring the Biases and Effectiveness of Content-Style Disentanglement
https://github.com/VITA-Group/GAN-LTH
공식 코드https://github.com/VLL-HD/conditional_INNs
공식 코드Conditional Invertible Neural Networks for Diverse Image-to-Image Translation
https://github.com/VinAIResearch/CPM
공식 코드Lipstick ain't enough: Beyond Color Matching for In-the-Wild Makeup Transfer
https://github.com/WonwoongCho/GDWCT
공식 코드Image-to-Image Translation via Group-wise Deep Whitening-and-Coloring Transformation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.