https://codeberg.org/fuchsfa/foundation-models-seismic-processing
공식 코드Foundation Models For Seismic Data Processing: An Extensive Review
Papers with Code 아카이브
Image-to-Image Translation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
- 38
- 보존된 평가 기록
- 195
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/1202kbs/gctm
공식 코드Generalized Consistency Trajectory Models for Image Manipulation
https://github.com/AAnoosheh/ComboGAN
공식 코드ComboGAN: Unrestrained Scalability for Image Domain Translation
https://github.com/AlamiMejjati/Unsupervised-Attention-guided-Image-to-Image-Translation
공식 코드https://github.com/Algolzw/SPAC-Deformable-Registration
공식 코드Stochastic Actor-Executor-Critic for Image-to-Image Translation
https://github.com/AliaksandrSiarohin/pose-gan
공식 코드https://github.com/Arnukk/CASPIAN
공식 코드https://github.com/ArshockAbedan/CS_MSc_Codes
공식 코드Multi-Modality Image Super-Resolution using Generative Adversarial Networks
https://github.com/BCV-Uniandes/SMIT
공식 코드https://github.com/BiQiWHU/CMFormer
공식 코드Learning Content-enhanced Mask Transformer for Domain Generalized Urban-Scene Segmentation
https://github.com/Boehringer-Ingelheim/stain-transfer
공식 코드A comparative evaluation of image-to-image translation methods for stain transfer in histopathology
https://github.com/CXH-Research/IRFormer
공식 코드https://github.com/Cardio-AI/detcyclegan_pytorch
공식 코드https://github.com/CherBass/ICAM
공식 코드ICAM: Interpretable Classification via Disentangled Representations and Feature Attribution Mapping
https://github.com/CompVis/net2net
공식 코드Network-to-Network Translation with Conditional Invertible Neural Networks
https://github.com/CompVis/taming-transformers
공식 코드https://github.com/CreativePapers/Learn-to-Synthesize-and-Synthesize-to-Learn
공식 코드https://github.com/CristianLazoQuispe/skin-lesion-segmentation-using-pix2pix
공식 코드Segmentation of skin lesions and their attributes using Generative Adversarial Networks
https://github.com/DavidAbramian/refacing
공식 코드Refacing: reconstructing anonymized facial features using GANs
https://github.com/DengPingFan/FS2K
공식 코드https://github.com/DengPingFan/FaceSketch-Awesome-List
공식 코드https://github.com/Elvinky/IEGAN
공식 코드Independent Encoder for Deep Hierarchical Unsupervised Image-to-Image Translation
https://github.com/EndlessSora/TSIT
공식 코드TSIT: A Simple and Versatile Framework for Image-to-Image Translation
https://github.com/EndlessSora/focal-frequency-loss
공식 코드https://github.com/ExplainableML/UncerGuidedI2I
공식 코드Uncertainty-Guided Progressive GANs for Medical Image Translation
https://github.com/ForawardStar/EDIT
공식 코드https://github.com/GaoLii/DSP
공식 코드DSP: Dual Soft-Paste for Unsupervised Domain Adaptive Semantic Segmentation
https://github.com/GeorgeEskandar/USIS-Unsupervised-Semantic-Image-Synthesis
공식 코드https://github.com/Guim3/IcGAN
공식 코드https://github.com/Ha0Tang/AsymmetricGAN
공식 코드https://github.com/Ha0Tang/AttentionGAN
공식 코드Attention-Guided Generative Adversarial Networks for Unsupervised Image-to-Image Translation
https://github.com/Ha0Tang/C2GAN
공식 코드https://github.com/Ha0Tang/GestureGAN
공식 코드Unified Generative Adversarial Networks for Controllable Image-to-Image Translation
https://github.com/Ha0Tang/LGGAN
공식 코드https://github.com/Ha0Tang/SelectionGAN
공식 코드Multi-Channel Attention Selection GANs for Guided Image-to-Image Translation
https://github.com/Hamsterrrrrrrrr/multiscale-ssh
공식 코드Multi-scale decomposition of sea surface height snapshots using machine learning
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.