Anycost Gan[CVPR 2021] Anycost GANs for Interactive Image Synthesis and Editing
Stars: ✭ 367 (+0.27%)
Contrastive Unpaired TranslationContrastive unpaired image-to-image translation, faster and lighter training than cyclegan (ECCV 2020, in PyTorch)
Stars: ✭ 822 (+124.59%)
CycleganSoftware that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.
Stars: ✭ 10,933 (+2887.16%)
Gesturegan[ACM MM 2018 Oral] GestureGAN for Hand Gesture-to-Gesture Translation in the Wild
Stars: ✭ 136 (-62.84%)
Lggan[CVPR 2020] Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation
Stars: ✭ 97 (-73.5%)
CoCosNet-v2CoCosNet v2: Full-Resolution Correspondence Learning for Image Translation
Stars: ✭ 312 (-14.75%)
CocosnetCross-domain Correspondence Learning for Exemplar-based Image Translation. (CVPR 2020 Oral)
Stars: ✭ 211 (-42.35%)
Pix2pixImage-to-image translation with conditional adversarial nets
Stars: ✭ 8,765 (+2294.81%)
FineganFineGAN: Unsupervised Hierarchical Disentanglement for Fine-grained Object Generation and Discovery
Stars: ✭ 240 (-34.43%)
Img2imgganImplementation of the paper : "Toward Multimodal Image-to-Image Translation"
Stars: ✭ 49 (-86.61%)
Anime2SketchA sketch extractor for anime/illustration.
Stars: ✭ 1,623 (+343.44%)
Faceswap GanA denoising autoencoder + adversarial losses and attention mechanisms for face swapping.
Stars: ✭ 3,099 (+746.72%)
TriangleGANTriangleGAN, ACM MM 2019.
Stars: ✭ 28 (-92.35%)
AODAOfficial implementation of "Adversarial Open Domain Adaptation for Sketch-to-Photo Synthesis"(WACV 2022/CVPRW 2021)
Stars: ✭ 44 (-87.98%)
Data Efficient Gans[NeurIPS 2020] Differentiable Augmentation for Data-Efficient GAN Training
Stars: ✭ 682 (+86.34%)
AttentionganAttentionGAN for Unpaired Image-to-Image Translation & Multi-Domain Image-to-Image Translation
Stars: ✭ 341 (-6.83%)
Tsit[ECCV 2020 Spotlight] A Simple and Versatile Framework for Image-to-Image Translation
Stars: ✭ 141 (-61.48%)
MixnmatchPytorch implementation of MixNMatch
Stars: ✭ 694 (+89.62%)
Fq GanOfficial implementation of FQ-GAN
Stars: ✭ 137 (-62.57%)
Image To Image Papers🦓<->🦒 🌃<->🌆 A collection of image to image papers with code (constantly updating)
Stars: ✭ 949 (+159.29%)
IganInteractive Image Generation via Generative Adversarial Networks
Stars: ✭ 3,845 (+950.55%)
Pytorch CycleganA clean and readable Pytorch implementation of CycleGAN
Stars: ✭ 558 (+52.46%)
St CganDataset and Code for our CVPR'18 paper ST-CGAN: "Stacked Conditional Generative Adversarial Networks for Jointly Learning Shadow Detection and Shadow Removal"
Stars: ✭ 13 (-96.45%)
L1stabilizer🎥 Video stabilization using L1-norm optimal camera paths.
Stars: ✭ 111 (-69.67%)
SMITPytorch implemenation of Stochastic Multi-Label Image-to-image Translation (SMIT), ICCV Workshops 2019.
Stars: ✭ 37 (-89.89%)
CycleGAN-gluon-mxnetthis repo attemps to reproduce Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks(CycleGAN) use gluon reimplementation
Stars: ✭ 31 (-91.53%)
pytorch-gansPyTorch implementation of GANs (Generative Adversarial Networks). DCGAN, Pix2Pix, CycleGAN, SRGAN
Stars: ✭ 21 (-94.26%)
chainer-pix2pixChainer implementation for Image-to-Image Translation Using Conditional Adversarial Networks
Stars: ✭ 40 (-89.07%)
Context Encoder[CVPR 2016] Unsupervised Feature Learning by Image Inpainting using GANs
Stars: ✭ 731 (+99.73%)
texturize🤖🖌️ Generate photo-realistic textures based on source images. Remix, remake, mashup! Useful if you want to create variations on a theme or elaborate on an existing texture.
Stars: ✭ 495 (+35.25%)
SdvSynthetic Data Generation for tabular, relational and time series data.
Stars: ✭ 360 (-1.64%)
Awesome-GAN-Resources🤖A list of resources to help anyone getting started with GANs 🤖
Stars: ✭ 90 (-75.41%)
DeepSIMOfficial PyTorch implementation of the paper: "DeepSIM: Image Shape Manipulation from a Single Augmented Training Sample" (ICCV 2021 Oral)
Stars: ✭ 389 (+6.28%)
Text To Image SynthesisPytorch implementation of Generative Adversarial Text-to-Image Synthesis paper
Stars: ✭ 288 (-21.31%)
coursera-gan-specializationProgramming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai
Stars: ✭ 277 (-24.32%)
simsgSemantic Image Manipulation using Scene Graphs (CVPR 2020)
Stars: ✭ 49 (-86.61%)
multitask-CycleGANPytorch implementation of multitask CycleGAN with auxiliary classification loss
Stars: ✭ 88 (-75.96%)
SDEditPyTorch implementation for SDEdit: Image Synthesis and Editing with Stochastic Differential Equations
Stars: ✭ 394 (+7.65%)
Pix2pixhdSynthesizing and manipulating 2048x1024 images with conditional GANs
Stars: ✭ 5,553 (+1417.21%)
ST-CGANDataset and Code for our CVPR'18 paper ST-CGAN: "Stacked Conditional Generative Adversarial Networks for Jointly Learning Shadow Detection and Shadow Removal"
Stars: ✭ 64 (-82.51%)
WGAN-GP-TensorFlowTensorFlow implementations of Wasserstein GAN with Gradient Penalty (WGAN-GP), Least Squares GAN (LSGAN), GANs with the hinge loss.
Stars: ✭ 42 (-88.52%)
Texturize🤖🖌️ Generate photo-realistic textures based on source images. Remix, remake, mashup! Useful if you want to create variations on a theme or elaborate on an existing texture.
Stars: ✭ 366 (+0%)
BicycleGAN-pytorchPytorch implementation of BicycleGAN with implementation details
Stars: ✭ 99 (-72.95%)
Generative models tutorial with demoGenerative Models Tutorial with Demo: Bayesian Classifier Sampling, Variational Auto Encoder (VAE), Generative Adversial Networks (GANs), Popular GANs Architectures, Auto-Regressive Models, Important Generative Model Papers, Courses, etc..
Stars: ✭ 276 (-24.59%)
CoMoGANCoMoGAN: continuous model-guided image-to-image translation. CVPR 2021 oral.
Stars: ✭ 139 (-62.02%)
IrwGANOfficial pytorch implementation of the IrwGAN for unaligned image-to-image translation
Stars: ✭ 33 (-90.98%)
Few Shot Patch Based TrainingThe official implementation of our SIGGRAPH 2020 paper Interactive Video Stylization Using Few-Shot Patch-Based Training
Stars: ✭ 313 (-14.48%)
AdverseBiNetImproving Document Binarization via Adversarial Noise-Texture Augmentation
Stars: ✭ 34 (-90.71%)
automatic-manga-colorizationUse keras.js and cyclegan-keras to colorize manga automatically. All computation in browser. Demo is online:
Stars: ✭ 20 (-94.54%)
BicycleGANTensorflow implementation of the NIPS paper "Toward Multimodal Image-to-Image Translation"
Stars: ✭ 30 (-91.8%)