Edge ConnectEdgeConnect: Structure Guided Image Inpainting using Edge Prediction, ICCV 2019 https://arxiv.org/abs/1901.00212
Stars: ✭ 2,163 (+2303.33%)
Fast SrganA Fast Deep Learning Model to Upsample Low Resolution Videos to High Resolution at 30fps
Stars: ✭ 417 (+363.33%)
Selectiongan[CVPR 2019 Oral] Multi-Channel Attention Selection GAN with Cascaded Semantic Guidance for Cross-View Image Translation
Stars: ✭ 366 (+306.67%)
BicycleganToward Multimodal Image-to-Image Translation
Stars: ✭ 1,215 (+1250%)
Gesturegan[ACM MM 2018 Oral] GestureGAN for Hand Gesture-to-Gesture Translation in the Wild
Stars: ✭ 136 (+51.11%)
Data Efficient Gans[NeurIPS 2020] Differentiable Augmentation for Data-Efficient GAN Training
Stars: ✭ 682 (+657.78%)
Deep-LearningIt contains the coursework and the practice I have done while learning Deep Learning.🚀 👨💻💥 🚩🌈
Stars: ✭ 21 (-76.67%)
DLSSDeep Learning Super Sampling with Deep Convolutional Generative Adversarial Networks.
Stars: ✭ 88 (-2.22%)
coursera-gan-specializationProgramming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai
Stars: ✭ 277 (+207.78%)
CycleganSoftware that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.
Stars: ✭ 10,933 (+12047.78%)
Anime2SketchA sketch extractor for anime/illustration.
Stars: ✭ 1,623 (+1703.33%)
Gans In ActionCompanion repository to GANs in Action: Deep learning with Generative Adversarial Networks
Stars: ✭ 748 (+731.11%)
AvatarGANGenerate Cartoon Images using Generative Adversarial Network
Stars: ✭ 24 (-73.33%)
gans-collection.torchTorch implementation of various types of GAN (e.g. DCGAN, ALI, Context-encoder, DiscoGAN, CycleGAN, EBGAN, LSGAN)
Stars: ✭ 53 (-41.11%)
SdvSynthetic Data Generation for tabular, relational and time series data.
Stars: ✭ 360 (+300%)
skip-thought-ganGenerating Text through Adversarial Training(GAN) using Skip-Thought Vectors
Stars: ✭ 44 (-51.11%)
Co Mod Gan[ICLR 2021, Spotlight] Large Scale Image Completion via Co-Modulated Generative Adversarial Networks
Stars: ✭ 46 (-48.89%)
Pacgan[NeurIPS 2018] [JSAIT] PacGAN: The power of two samples in generative adversarial networks
Stars: ✭ 67 (-25.56%)
3d Recgan🔥3D-RecGAN in Tensorflow (ICCV Workshops 2017)
Stars: ✭ 116 (+28.89%)
Doppelganger[IMC 2020 (Best Paper Finalist)] Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions
Stars: ✭ 97 (+7.78%)
Colorizing With GansGrayscale Image Colorization with Generative Adversarial Networks. https://arxiv.org/abs/1803.05400
Stars: ✭ 209 (+132.22%)
CocosnetCross-domain Correspondence Learning for Exemplar-based Image Translation. (CVPR 2020 Oral)
Stars: ✭ 211 (+134.44%)
Anycost Gan[CVPR 2021] Anycost GANs for Interactive Image Synthesis and Editing
Stars: ✭ 367 (+307.78%)
FineganFineGAN: Unsupervised Hierarchical Disentanglement for Fine-grained Object Generation and Discovery
Stars: ✭ 240 (+166.67%)
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 (+206.67%)
Contrastive Unpaired TranslationContrastive unpaired image-to-image translation, faster and lighter training than cyclegan (ECCV 2020, in PyTorch)
Stars: ✭ 822 (+813.33%)
Faceswap GanA denoising autoencoder + adversarial losses and attention mechanisms for face swapping.
Stars: ✭ 3,099 (+3343.33%)
TaganAn official PyTorch implementation of the paper "Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language", NeurIPS 2018
Stars: ✭ 97 (+7.78%)
IseebetteriSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs | Published in Springer Journal of Computational Visual Media, September 2020, Tsinghua University Press
Stars: ✭ 202 (+124.44%)
Von[NeurIPS 2018] Visual Object Networks: Image Generation with Disentangled 3D Representation.
Stars: ✭ 497 (+452.22%)
Generative adversarial networks 101Keras implementations of Generative Adversarial Networks. GANs, DCGAN, CGAN, CCGAN, WGAN and LSGAN models with MNIST and CIFAR-10 datasets.
Stars: ✭ 138 (+53.33%)
GifGIF is a photorealistic generative face model with explicit 3D geometric and photometric control.
Stars: ✭ 233 (+158.89%)
pytorch-gansPyTorch implementation of GANs (Generative Adversarial Networks). DCGAN, Pix2Pix, CycleGAN, SRGAN
Stars: ✭ 21 (-76.67%)
PESROfficial code (Pytorch) for paper Perception-Enhanced Single Image Super-Resolution via Relativistic Generative Networks
Stars: ✭ 28 (-68.89%)
DiscoGAN-TFTensorflow Implementation of DiscoGAN
Stars: ✭ 57 (-36.67%)
CIPS-3D3D-aware GANs based on NeRF (arXiv).
Stars: ✭ 562 (+524.44%)
SSVEP-Neural-Generative-ModelsCode to accompany our International Joint Conference on Neural Networks (IJCNN) paper entitled - Simulating Brain Signals: Creating Synthetic EEG Data via Neural-Based Generative Models for Improved SSVEP Classification
Stars: ✭ 37 (-58.89%)
pytorch-GANMy pytorch implementation for GAN
Stars: ✭ 12 (-86.67%)
bmuseganCode for “Convolutional Generative Adversarial Networks with Binary Neurons for Polyphonic Music Generation”
Stars: ✭ 58 (-35.56%)
Deep-FakesNo description or website provided.
Stars: ✭ 88 (-2.22%)
awesome-generative-deep-artA curated list of generative deep learning tools, works, models, etc. for artistic uses
Stars: ✭ 172 (+91.11%)
Pose2vecA Repository for maintaining various human skeleton preprocessing steps in numpy and tensorflow along with tensorflow model to learn pose embeddings.
Stars: ✭ 25 (-72.22%)
DeepEchoSynthetic Data Generation for mixed-type, multivariate time series.
Stars: ✭ 44 (-51.11%)
DCGAN-PytorchA Pytorch implementation of "Deep Convolutional Generative Adversarial Networks"
Stars: ✭ 23 (-74.44%)
MAD-GAN-MLCAMPRepository for MAD-GAN Paper done in ML CAMP Jeju
Stars: ✭ 17 (-81.11%)
timegan-pytorchThis repository is a non-official implementation of TimeGAN (Yoon et al., NIPS2019) using PyTorch.
Stars: ✭ 46 (-48.89%)
ganbertEnhancing the BERT training with Semi-supervised Generative Adversarial Networks
Stars: ✭ 205 (+127.78%)
text2image-benchmarkPerformance comparison of existing GAN based Text To Image algorithms. (GAN-CLS, StackGAN, TAC-GAN)
Stars: ✭ 25 (-72.22%)
MMD-GANImproving MMD-GAN training with repulsive loss function
Stars: ✭ 82 (-8.89%)
GraphCNN-GANGraph-convolutional GAN for point cloud generation. Code from ICLR 2019 paper Learning Localized Generative Models for 3D Point Clouds via Graph Convolution
Stars: ✭ 50 (-44.44%)