Lggan[CVPR 2020] Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation
Stars: ✭ 97 (-28.68%)
Selectiongan[CVPR 2019 Oral] Multi-Channel Attention Selection GAN with Cascaded Semantic Guidance for Cross-View Image Translation
Stars: ✭ 366 (+169.12%)
CoCosNet-v2CoCosNet v2: Full-Resolution Correspondence Learning for Image Translation
Stars: ✭ 312 (+129.41%)
Anycost Gan[CVPR 2021] Anycost GANs for Interactive Image Synthesis and Editing
Stars: ✭ 367 (+169.85%)
CycleganSoftware that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.
Stars: ✭ 10,933 (+7938.97%)
Contrastive Unpaired TranslationContrastive unpaired image-to-image translation, faster and lighter training than cyclegan (ECCV 2020, in PyTorch)
Stars: ✭ 822 (+504.41%)
TriangleGANTriangleGAN, ACM MM 2019.
Stars: ✭ 28 (-79.41%)
CocosnetCross-domain Correspondence Learning for Exemplar-based Image Translation. (CVPR 2020 Oral)
Stars: ✭ 211 (+55.15%)
FineganFineGAN: Unsupervised Hierarchical Disentanglement for Fine-grained Object Generation and Discovery
Stars: ✭ 240 (+76.47%)
MixnmatchPytorch implementation of MixNMatch
Stars: ✭ 694 (+410.29%)
Data Efficient Gans[NeurIPS 2020] Differentiable Augmentation for Data-Efficient GAN Training
Stars: ✭ 682 (+401.47%)
Image To Image Papers🦓<->🦒 🌃<->🌆 A collection of image to image papers with code (constantly updating)
Stars: ✭ 949 (+597.79%)
Img2imgganImplementation of the paper : "Toward Multimodal Image-to-Image Translation"
Stars: ✭ 49 (-63.97%)
Pix2pixImage-to-image translation with conditional adversarial nets
Stars: ✭ 8,765 (+6344.85%)
Anime2SketchA sketch extractor for anime/illustration.
Stars: ✭ 1,623 (+1093.38%)
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 (+263.97%)
AODAOfficial implementation of "Adversarial Open Domain Adaptation for Sketch-to-Photo Synthesis"(WACV 2022/CVPRW 2021)
Stars: ✭ 44 (-67.65%)
Fq GanOfficial implementation of FQ-GAN
Stars: ✭ 137 (+0.74%)
Faceswap GanA denoising autoencoder + adversarial losses and attention mechanisms for face swapping.
Stars: ✭ 3,099 (+2178.68%)
Tsit[ECCV 2020 Spotlight] A Simple and Versatile Framework for Image-to-Image Translation
Stars: ✭ 141 (+3.68%)
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 (+102.94%)
coursera-gan-specializationProgramming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai
Stars: ✭ 277 (+103.68%)
AttentionganAttentionGAN for Unpaired Image-to-Image Translation & Multi-Domain Image-to-Image Translation
Stars: ✭ 341 (+150.74%)
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 (+169.12%)
Generative Evaluation PrdcCode base for the precision, recall, density, and coverage metrics for generative models. ICML 2020.
Stars: ✭ 117 (-13.97%)
Fast SrganA Fast Deep Learning Model to Upsample Low Resolution Videos to High Resolution at 30fps
Stars: ✭ 417 (+206.62%)
3d Recgan🔥3D-RecGAN in Tensorflow (ICCV Workshops 2017)
Stars: ✭ 116 (-14.71%)
IganInteractive Image Generation via Generative Adversarial Networks
Stars: ✭ 3,845 (+2727.21%)
GansformerGenerative Adversarial Transformers
Stars: ✭ 421 (+209.56%)
Mlds2018springMachine Learning and having it Deep and Structured (MLDS) in 2018 spring
Stars: ✭ 124 (-8.82%)
HidtOfficial repository for the paper "High-Resolution Daytime Translation Without Domain Labels" (CVPR2020, Oral)
Stars: ✭ 513 (+277.21%)
SeqganA simplified PyTorch implementation of "SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient." (Yu, Lantao, et al.)
Stars: ✭ 502 (+269.12%)
Pytorch CycleganA clean and readable Pytorch implementation of CycleGAN
Stars: ✭ 558 (+310.29%)
SeanSEAN: Image Synthesis with Semantic Region-Adaptive Normalization (CVPR 2020, Oral)
Stars: ✭ 387 (+184.56%)
Von[NeurIPS 2018] Visual Object Networks: Image Generation with Disentangled 3D Representation.
Stars: ✭ 497 (+265.44%)
Cramer GanTensorflow Implementation on "The Cramer Distance as a Solution to Biased Wasserstein Gradients" (https://arxiv.org/pdf/1705.10743.pdf)
Stars: ✭ 123 (-9.56%)
Delving Deep Into GansGenerative Adversarial Networks (GANs) resources sorted by citations
Stars: ✭ 834 (+513.24%)
CadganICML 2019. Turn a pre-trained GAN model into a content-addressable model without retraining.
Stars: ✭ 19 (-86.03%)
Gans In ActionCompanion repository to GANs in Action: Deep learning with Generative Adversarial Networks
Stars: ✭ 748 (+450%)
Mnist inception scoreTraining a MNIST classifier, and use it to compute inception score (ICP)
Stars: ✭ 25 (-81.62%)
Co Mod Gan[ICLR 2021, Spotlight] Large Scale Image Completion via Co-Modulated Generative Adversarial Networks
Stars: ✭ 46 (-66.18%)
Matlab GanMATLAB implementations of Generative Adversarial Networks -- from GAN to Pixel2Pixel, CycleGAN
Stars: ✭ 63 (-53.68%)
Fewshot Face Translation GanGenerative adversarial networks integrating modules from FUNIT and SPADE for face-swapping.
Stars: ✭ 705 (+418.38%)
Dna GanDNA-GAN: Learning Disentangled Representations from Multi-Attribute Images
Stars: ✭ 65 (-52.21%)
Dcgan TensorflowA Tensorflow implementation of Deep Convolutional Generative Adversarial Networks trained on Fashion-MNIST, CIFAR-10, etc.
Stars: ✭ 70 (-48.53%)
IcfaceICface: Interpretable and Controllable Face Reenactment Using GANs
Stars: ✭ 122 (-10.29%)
Markov Chain GanCode for "Generative Adversarial Training for Markov Chains" (ICLR 2017 Workshop)
Stars: ✭ 76 (-44.12%)
TorchganResearch Framework for easy and efficient training of GANs based on Pytorch
Stars: ✭ 1,156 (+750%)
Pytorch Pix2pixPytorch implementation of pix2pix for various datasets.
Stars: ✭ 74 (-45.59%)
GdwctOfficial PyTorch implementation of GDWCT (CVPR 2019, oral)
Stars: ✭ 122 (-10.29%)
Generating Devanagari Using DrawPyTorch implementation of DRAW: A Recurrent Neural Network For Image Generation trained on Devanagari dataset.
Stars: ✭ 82 (-39.71%)
AliceNIPS 2017: ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching
Stars: ✭ 80 (-41.18%)