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image-generation
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Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.
computer-vision
deep-learning
computer-graphics
torch
generative-adversarial-network
gan
image-manipulation
image-generation
gans
pix2pix
cyclegan
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Updated
Mar 4, 2020 - Lua
lkiani
commented
May 18, 2019
Which images should I use in the evaluation code?
I compared the generated images with Ground truth images and generated images with labels but got an error and the result of all the parameters was zero.
Generated images should be converted to label?
Solving this problem is very important to me.
thank you
. DeepNude的算法以及通用GAN图像生成的理论与实践研究。
dcgan
vae
image-generation
pix2pix
image-to-image
nerual-style
cycle-gan
deepface
deepfakes
tensorflow2
style-gan
deepnude
zao
sin-gan
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Updated
Mar 4, 2020 - Python
Easily create PDF and images in Symfony by converting html using webkit
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Updated
Feb 29, 2020 - PHP
TensorFlow Implementation of Unsupervised Cross-Domain Image Generation
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Updated
Feb 29, 2020 - Python
pixeline
commented
Jan 31, 2020
I'm working on a Sapper/Svelte PWA.
The images are to sit in a "static/images/app-icons" folder.
Sapper uses a template.html static html file to generate the SPA index.html
If i do
pwa-asset-generator mathr-icon.png ./static/images/app-icons -o false -m static/site.webmanifest -i src/template.html -f trueThe image path is of the like:
<link rel="apple-touch-icA clean and readable Pytorch implementation of CycleGAN
computer-vision
deep-learning
computer-graphics
image-processing
pytorch
artificial-intelligence
generative-adversarial-network
image-generation
cyclegan
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Updated
Mar 3, 2020 - Python
Pytorch implementation of MixNMatch
deep-learning
pytorch
image-manipulation
image-generation
gans
fine-grained
disentangled-representations
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Updated
Mar 2, 2020 - Python
[CVPR 2019 Oral] Multi-Channel Attention Selection GAN with Cascaded Semantic Guidance for Cross-View Image Translation
computer-vision
deep-learning
computer-graphics
pytorch
generative-adversarial-network
image-manipulation
image-generation
gans
image-translation
dayton
adversarial-learning
image-to-image-translation
semantic-maps
cross-view
cvpr-2019
cvpr2019
cvpr19
cvusa-dataset
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Updated
Mar 4, 2020 - Python
Pytorch implementation of Generative Adversarial Text-to-Image Synthesis paper
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Updated
Mar 4, 2020 - Python
Tensorflow implementation for Conditional Convolutional Adversarial Networks.
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Updated
Feb 23, 2020 - Python
AttentionGAN for Unpaired Image-to-Image Translation & Multi-Domain Image-to-Image Translation
computer-vision
deep-learning
geometry
pytorch
image-generation
multi-domain
gans
adversarial-networks
image-translation
attention-model
cyclegan
image-to-image-translation
ijcnn
unpaired
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Updated
Mar 4, 2020 - Python
Pytorch implementation of "One-Sided Unsupervised Domain Mapping" NIPS 2017
computer-vision
deep-learning
pytorch
gan
image-manipulation
image-generation
unsupervised-learning
computer-vision-ai
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Updated
Mar 2, 2020 - Python
Theano reimplementation of pixelCNN architecture
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Updated
Feb 5, 2020 - Python
Image Inpainting via Generative Multi-column Convolutional Neural Networks
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Updated
Mar 3, 2020 - Python
Code for APDrawingGAN: Generating Artistic Portrait Drawings from Face Photos with Hierarchical GANs (CVPR 2019 Oral)
computer-vision
deep-learning
computer-graphics
pytorch
gan
face
image-generation
image-synthesis
apdrawinggan
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Updated
Mar 1, 2020 - Python
FineGAN: Unsupervised Hierarchical Disentanglement for Fine-grained Object Generation and Discovery
computer-vision
deep-learning
pytorch
generative-adversarial-network
image-manipulation
image-generation
gans
fine-grained
disentangled-representations
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Updated
Mar 2, 2020 - Python
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Updated
Feb 19, 2020 - Python
StoryGAN: A Sequential Conditional GAN for Story Visualization
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Updated
Mar 1, 2020 - Python
A collection of arbitrary text to image papers with code (constantly updating)
image
collection
code
dialog
generative-adversarial-network
gan
image-generation
curated-list
scene-graph
text-to-image
image-synthesis
text2image
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Updated
Mar 1, 2020
Code for TileGAN: Synthesis of Large-Scale Non-Homogeneous Textures (SIGGRAPH 2019)
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Updated
Mar 4, 2020 - Python
Pytorch implementation of "One-Shot Unsupervised Cross Domain Translation" NIPS 2018
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Updated
Mar 4, 2020 - Python
A PyTorch implementation of the paper: Specifying Object Attributes and Relations in Interactive Scene Generation
machine-learning
computer-vision
deep-learning
pytorch
image-generation
scene-graph
ms-coco
iccv2019
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Updated
Feb 22, 2020 - Python
PyTorch implementation of Lagging Inference Networks and Posterior Collapse in Variational Autoencoders
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Updated
Feb 21, 2020 - Python
[ACM MM 2018 Oral] GestureGAN for Hand Gesture-to-Gesture Translation in the Wild
computer-vision
deep-learning
pytorch
generative-adversarial-network
generative-model
image-manipulation
image-generation
gans
image-translation
hand-gestures
dayton
image-to-image-translation
semantic-maps
hand-gesture
controllable
acmmm2018
cross-view
cvusa-dataset
gesture-translation
hand-skeletons
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Updated
Mar 2, 2020 - Python
Machine Learning and having it Deep and Structured (MLDS) in 2018 spring
reinforcement-learning
spring
chatbot
generative-adversarial-network
gan
policy-gradient
seq2seq
image-generation
sequence-to-sequence
chat-bot
ntu
deep-q-network
text-to-image
actor-critic
video-captioning
2018
chinese-chatbot
hung-yi-lee
mlds2018spring
mlds
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Updated
Feb 24, 2020 - Python
akarduni
commented
Feb 5, 2020
So I am very interested in the manual editing features of this model that is shown in the video. Is there more documentation available on how to run that?
Implemented Variational Autoencoder generative model in Keras for image generation and its latent space visualization on MNIST and CIFAR10 datasets
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Updated
Feb 23, 2020 - Python
Facial Expression Editing with Controllable Expression Intensity
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Updated
Mar 2, 2020 - Python
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Hi, thanks for your great work.
I'm trying to apply cyclegan on my own custom anime dataset to learn facial expression transfer.
My dataset includes 2000 sad and 2000 happy images.
I run the training process for about 100k iterations.
The problem is that I only see some small changes specially in mouth part. Do you have any suggestion? How can I make network more flexible for changing di