SuperStyleNetSuperStyleNet: Deep Image Synthesis with Superpixel Based Style Encoder (BMVC 2021)
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text-to-imageRe-implementation of https://github.com/zsdonghao/text-to-image
Stars: ✭ 25 (-65.28%)
external-internal-inpainting[CVPR 2021] EII: Image Inpainting with External-Internal Learning and Monochromic Bottleneck
Stars: ✭ 95 (+31.94%)
CLIP-Guided-DiffusionJust playing with getting CLIP Guided Diffusion running locally, rather than having to use colab.
Stars: ✭ 328 (+355.56%)
cDCGANPyTorch implementation of Conditional Deep Convolutional Generative Adversarial Networks (cDCGAN)
Stars: ✭ 49 (-31.94%)
Conditional-SeqGAN-TensorflowConditional Sequence Generative Adversarial Network trained with policy gradient, Implementation in Tensorflow
Stars: ✭ 47 (-34.72%)
Sketch2Color-anime-translationGiven a simple anime line-art sketch the model outputs a decent colored anime image using Conditional-Generative Adversarial Networks (C-GANs) concept.
Stars: ✭ 90 (+25%)
coursera-gan-specializationProgramming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai
Stars: ✭ 277 (+284.72%)
Data-WhispererAn NLP text to vizualization builder for Tableau.
Stars: ✭ 13 (-81.94%)
Pix2PixImage to Image Translation using Conditional GANs (Pix2Pix) implemented using Tensorflow 2.0
Stars: ✭ 29 (-59.72%)
feed forward vqgan clipFeed forward VQGAN-CLIP model, where the goal is to eliminate the need for optimizing the latent space of VQGAN for each input prompt
Stars: ✭ 135 (+87.5%)
gans-2.0Generative Adversarial Networks in TensorFlow 2.0
Stars: ✭ 76 (+5.56%)
Everybody-dance-nowImplementation of paper everybody dance now for Deep learning course project
Stars: ✭ 22 (-69.44%)
idgDocument image generator
Stars: ✭ 40 (-44.44%)
ru-dalleGenerate images from texts. In Russian
Stars: ✭ 1,606 (+2130.56%)
gpuvmemGPU Framework for Radio Astronomical Image Synthesis
Stars: ✭ 27 (-62.5%)
universum-contractstext-to-image generation gems / libraries incl. moonbirds, cyberpunks, coolcats, shiba inu doge, nouns & more
Stars: ✭ 17 (-76.39%)
VQGAN-CLIPJust playing with getting VQGAN+CLIP running locally, rather than having to use colab.
Stars: ✭ 2,369 (+3190.28%)
Seg2EyeOfficial implementation of "Content-Consistent Generation of Realistic Eyes with Style", ICCW 2019
Stars: ✭ 26 (-63.89%)
CoCosNet-v2CoCosNet v2: Full-Resolution Correspondence Learning for Image Translation
Stars: ✭ 312 (+333.33%)
pix2pixThis project uses a conditional generative adversarial network (cGAN) named Pix2Pix for the Image to image translation task.
Stars: ✭ 28 (-61.11%)
NovelViewSynthesis-TensorFlowA TensorFlow implementation of a simple Novel View Synthesis model on ShapeNet (cars and chairs), KITTI, and Synthia.
Stars: ✭ 47 (-34.72%)
gan-ensemblingInvert and perturb GAN images for test-time ensembling
Stars: ✭ 93 (+29.17%)
Dalle PytorchImplementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch
Stars: ✭ 3,661 (+4984.72%)
CogViewText-to-Image generation. The repo for NeurIPS 2021 paper "CogView: Mastering Text-to-Image Generation via Transformers".
Stars: ✭ 708 (+883.33%)
VQGAN-CLIP-DockerZero-Shot Text-to-Image Generation VQGAN+CLIP Dockerized
Stars: ✭ 58 (-19.44%)
clip-guided-diffusionA CLI tool/python module for generating images from text using guided diffusion and CLIP from OpenAI.
Stars: ✭ 260 (+261.11%)
text2paintingConvert text into beautiful artistic images
Stars: ✭ 55 (-23.61%)
KoDALLE🇰🇷 Text to Image in Korean
Stars: ✭ 55 (-23.61%)
im2txt2imI2T2I: Text-to-Image Synthesis with textual data augmentation
Stars: ✭ 29 (-59.72%)
keras-text-to-imageTranslate text to image in Keras using GAN and Word2Vec as well as recurrent neural networks
Stars: ✭ 60 (-16.67%)
pytorch-ACSCPUnofficial implementation of "Crowd Counting via Adversarial Cross-Scale Consistency Pursuit" with pytorch - CVPR 2018
Stars: ✭ 18 (-75%)
ACSCP cGANCode implementation for paper that "ACSCS: Crowd Counting via Adversarial Cross-Scale Consistency Pursuit"; This is method of Crowd counting by conditional generation adversarial networks
Stars: ✭ 36 (-50%)
SLE-GANTowards Faster and Stabilized GAN Training for High-fidelity Few-shot Image Synthesis
Stars: ✭ 53 (-26.39%)
Fundus ReviewOfficial website of our paper: Applications of Deep Learning in Fundus Images: A Review. Newly-released datasets and recently-published papers will be updated regularly.
Stars: ✭ 64 (-11.11%)
WGAN-GP-TensorFlowTensorFlow implementations of Wasserstein GAN with Gradient Penalty (WGAN-GP), Least Squares GAN (LSGAN), GANs with the hinge loss.
Stars: ✭ 42 (-41.67%)
ArtGANTensorflow codes for our ICIP-17 and arXiv-1708.09533 works: "ArtGAN: Artwork Synthesis with Conditional Categorial GAN" & "Learning a Generative Adversarial Network for High Resolution Artwork Synthesis "
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OpenShapesA data-driven approach for interactively synthesizing diverse images from semantic label maps.
Stars: ✭ 39 (-45.83%)