https://github.com/Cold-Winter/BachGAN
Semantic Image Synthesis with Spatially-Adaptive Normalization
Papers with Code 아카이브
Image-to-Image Translation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 11
- 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/CorneliusHsiao/FoodMethodGAN
https://github.com/CoryRJ/cycleGAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/CreativeCodingLab/DeepIllumination
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/CrossEntropy/Gesture-images-recognition-ResidualNetwork
https://github.com/CryptoSalamander/pytorch_paper_implementation
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/D-X-Y/ResNeXt-DenseNet
https://github.com/DLHacks/pix2pix_PAN
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/DMarwan/NutricIA
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/DableUTeeF/keras-efficientnet
https://github.com/Daeijavad/MAD-GAN
https://github.com/DaikiTanak/manifold_mixup
https://github.com/DarkGeekMS/Tensorflow-GANs-Architectures-Implementation
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/Darth-Kronos/Unsupervised-Domain-Adaptation
https://github.com/DavidCastilloAlvarado/U-NET_AUTOENCODER
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/Deci-AI/super-gradients
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/DeepMIALab/AI-FFPE
Contrastive Learning for Unpaired Image-to-Image Translation
https://github.com/DeepMark/deepmark
https://github.com/DeepikaKaranji/CycleGAN-Unpaired-Image-translation
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/Demonhesusheng/Reid
Joint Discriminative and Generative Learning for Person Re-identification
https://github.com/Deopoler/DCLGAN-Keras
Dual Contrastive Learning for Unsupervised Image-to-Image Translation
https://github.com/DogeZen/resnet2onnx2tensorrt
https://github.com/Dominioncher/smart-sketch
Semantic Image Synthesis with Spatially-Adaptive Normalization
https://github.com/DrRyanHuang/VGGNet
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Duplums/bhb10k-dl-benchmark
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/E-DEEP/PapersReview
https://github.com/EdenMelaku/Transfer-Learning-Pytorch-Implementation
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/EdenMelaku/Transfer-Learning-Pytorch-Implmentation
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/EiroaMD/final_project_IH_pneumonia
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Electro1111/COVID_19_CXR_CLASSIFICATION
https://github.com/Elman295/Maximum-Classifier-Discrepancy-for-Unsupervised-Domain-Adaptation
Maximum Classifier Discrepancy for Unsupervised Domain Adaptation
https://github.com/Elman295/Unsupervised-Domain-Adaptation-by-Backpropagation-
https://github.com/Emir-Liu/Cycle-GAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/EngineeringSapien/NarutoCV
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/EricAlcaide/MiniFold
https://github.com/EstherBear/implementation-of-pruning-filters
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.