woozzu / Tagan
Licence: apache-2.0
An official PyTorch implementation of the paper "Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language", NeurIPS 2018
Stars: ✭ 97
Programming Languages
python
139335 projects - #7 most used programming language
Projects that are alternatives of or similar to Tagan
A Pytorch Tutorial To Super Resolution
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network | a PyTorch Tutorial to Super-Resolution
Stars: ✭ 157 (+61.86%)
Mutual labels: gan, generative-adversarial-network, gans
Doppelganger
[IMC 2020 (Best Paper Finalist)] Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions
Stars: ✭ 97 (+0%)
Mutual labels: gan, generative-adversarial-network, gans
Iseebetter
iSeeBetter: 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 (+108.25%)
Mutual labels: gan, generative-adversarial-network, gans
Pytorch Cyclegan And Pix2pix
Image-to-Image Translation in PyTorch
Stars: ✭ 16,477 (+16886.6%)
Mutual labels: gan, generative-adversarial-network, gans
Pacgan
[NeurIPS 2018] [JSAIT] PacGAN: The power of two samples in generative adversarial networks
Stars: ✭ 67 (-30.93%)
Mutual labels: gan, generative-adversarial-network, gans
Generative adversarial networks 101
Keras implementations of Generative Adversarial Networks. GANs, DCGAN, CGAN, CCGAN, WGAN and LSGAN models with MNIST and CIFAR-10 datasets.
Stars: ✭ 138 (+42.27%)
Mutual labels: gan, generative-adversarial-network, gans
Gif
GIF is a photorealistic generative face model with explicit 3D geometric and photometric control.
Stars: ✭ 233 (+140.21%)
Mutual labels: gan, generative-adversarial-network, gans
Cyclegan
Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.
Stars: ✭ 10,933 (+11171.13%)
Mutual labels: gan, generative-adversarial-network, gans
Faceswap Gan
A denoising autoencoder + adversarial losses and attention mechanisms for face swapping.
Stars: ✭ 3,099 (+3094.85%)
Mutual labels: gan, generative-adversarial-network, gans
DLSS
Deep Learning Super Sampling with Deep Convolutional Generative Adversarial Networks.
Stars: ✭ 88 (-9.28%)
Mutual labels: generative-adversarial-network, gan, gans
AvatarGAN
Generate Cartoon Images using Generative Adversarial Network
Stars: ✭ 24 (-75.26%)
Mutual labels: generative-adversarial-network, gan, gans
Anycost Gan
[CVPR 2021] Anycost GANs for Interactive Image Synthesis and Editing
Stars: ✭ 367 (+278.35%)
Mutual labels: gan, generative-adversarial-network, gans
Sdv
Synthetic Data Generation for tabular, relational and time series data.
Stars: ✭ 360 (+271.13%)
Mutual labels: gan, generative-adversarial-network, gans
Gans In Action
Companion repository to GANs in Action: Deep learning with Generative Adversarial Networks
Stars: ✭ 748 (+671.13%)
Mutual labels: gan, generative-adversarial-network, gans
Calogan
Generative Adversarial Networks for High Energy Physics extended to a multi-layer calorimeter simulation
Stars: ✭ 87 (-10.31%)
Mutual labels: gan, generative-adversarial-network
Co Mod Gan
[ICLR 2021, Spotlight] Large Scale Image Completion via Co-Modulated Generative Adversarial Networks
Stars: ✭ 46 (-52.58%)
Mutual labels: generative-adversarial-network, gans
Sprint gan
Privacy-preserving generative deep neural networks support clinical data sharing
Stars: ✭ 92 (-5.15%)
Mutual labels: gan, generative-adversarial-network
Acgan Pytorch
Pytorch implementation of Conditional Image Synthesis with Auxiliary Classifier GANs
Stars: ✭ 57 (-41.24%)
Mutual labels: gan, generative-adversarial-network
Bringing Old Photos Back To Life
Bringing Old Photo Back to Life (CVPR 2020 oral)
Stars: ✭ 9,525 (+9719.59%)
Mutual labels: generative-adversarial-network, gans
Gandlf
Generative Adversarial Networks in Keras
Stars: ✭ 46 (-52.58%)
Mutual labels: gan, generative-adversarial-network
Text-Adaptive Generative Adversarial Network (TAGAN)
A PyTorch implementation of the paper "Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language". This code implements a Text-Adaptive Generative Adversarial Network (TAGAN) for manipulating images with natural language.
Requirements
Pretrained word vectors for fastText
Download a pretrained English word vectors. You can see the list of pretrained vectors on this page.
Datasets
The caption data is from this repository. After downloading, modify CONFIG file so that all paths of the datasets point to the data you downloaded.
Pretrained models
- Oxford-102 flowers: flowers_G.pth
- Caltech-200 birds: birds_G.pth
Please put these files in ./models/ folder.
Run
-
scripts/preprocess_caption.sh
Preprocess caption data using fastText embedding. You only need to run it once before training. -
scripts/train_[flowers/birds].sh
Train a network. If you want to change arguments, please refer totrain.py. -
scripts/test_[flowers/birds].sh
Test a trained network. After running it, please see./test/result_[flowers/birds]/index.html.
Results
Citation
Please cite our paper when you use this code.
@inproceedings{nam2018tagan,
title={Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language},
author={Nam, Seonghyeon and Kim, Yunji and Kim, Seon Joo},
booktitle={Advances in Neural Information Processing Systems (NeurIPS)},
year={2018}
}
Contact
Please contact [email protected] if you have any question about this work.
Note that the project description data, including the texts, logos, images, and/or trademarks,
for each open source project belongs to its rightful owner.
If you wish to add or remove any projects, please contact us at [email protected].