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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/Beny-Maleki/Pix2PixTorch

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/Bingwen-Hu/DRIT

Diverse Image-to-Image Translation via Disentangled Representations

https://github.com/Blade6570/Learningimage-to-imagetranslationusingpairedandunpairedtrainingsamples

Learning image-to-image translation using paired and unpaired training samples

https://github.com/BrookInternSOMA/pix2pix-barcode

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/Burf/ResNet-Tensorflow2

Deep Residual Learning for Image Recognition

https://github.com/CNC-IISER-BHOPAL/Any-Body-Can-Dance

Everybody Dance Now

https://github.com/COMP6248-Reproducability-Challenge/Transfer-Learning

Transfer Learning for Related Reinforcement Learning Tasks via Image-to-Image Translation

https://github.com/CS2470FinalProject/X-GAN

XGAN: Unsupervised Image-to-Image Translation for Many-to-Many Mappings

https://github.com/CV-Reimplementation/FUNIT-Reimplementation

Few-Shot Unsupervised Image-to-Image Translation

https://github.com/CV-Reimplementation/ResViT-Reimplementation

ResViT: Residual vision transformers for multi-modal medical image synthesis

https://github.com/CVxTz/face_age_gender

Deep Residual Learning for Image Recognition

https://github.com/CXH-Research/UIE-UnFold

Implicit Multi-Spectral Transformer: An Lightweight and Effective Visible to Infrared Image Translation Model

https://github.com/CanshangD/ResNet_tensorflow2.0

Deep Residual Learning for Image Recognition

https://github.com/Carl0520/ADDA-pytorch

Adversarial Discriminative Domain Adaptation

https://github.com/Carl0520/DANN_pytorch-

Unsupervised Domain Adaptation by Backpropagation

https://github.com/CarpdiemLiang/style_transfer

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/CellSMB/EM-net

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/ChandhiniG/Generate-Stylized-Image-from-Edges

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/ChangweiZhang/Awesome-WindowsML-ONNX-Models

Deep Residual Learning for Image Recognition

https://github.com/Chemino/UGATIT-Paddle

U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation

https://github.com/ChrisAllenMing/Mixup_for_UDA

Unsupervised Domain Adaptation by Backpropagation

https://github.com/CocoSungMin/Gachon_SW_Colorization_Contest

Deep Residual Learning for Image Recognition

https://github.com/CodeChefVIT/VOID

Deep Residual Learning for Image Recognition

https://github.com/Cold-Winter/BachGAN

Semantic Image Synthesis with Spatially-Adaptive Normalization

https://github.com/CorneliusHsiao/FoodMethodGAN

Deep Residual Learning for Image Recognition

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

Deep Residual Learning for Image Recognition

https://github.com/CryptoSalamander/pytorch_paper_implementation

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/D-X-Y/ResNeXt-DenseNet

Deep Residual Learning for Image Recognition

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

Deep Residual Learning for Image Recognition

https://github.com/Daeijavad/MAD-GAN

Multi-Agent Diverse Generative Adversarial Networks

https://github.com/DaikiTanak/manifold_mixup

Deep Residual Learning for Image Recognition

https://github.com/DarkGeekMS/Tensorflow-GANs-Architectures-Implementation

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.