ALAE
stargan-v2
ALAE | stargan-v2 | |
---|---|---|
1 | 1 | |
3,509 | 3,491 | |
- | 0.9% | |
0.0 | 0.0 | |
almost 4 years ago | over 1 year ago | |
Python | Python | |
- | GNU General Public License v3.0 or later |
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ALAE
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[D] How do I make a model which takes a bedroom image as input give an output of different design of bedroom related to input image?
source link: https://github.com/podgorskiy/ALAE
stargan-v2
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How to Run stargan2 on Google Colab
This version of StarGAN2 (coined as 'Post-modern Style Transfer') is intended mostly for fellow artists, who rarely look at scientific metrics, but rather need a working creative tool. At least, this is what I use nearly daily myself. Here are few pieces, made with it: Terminal Blink, Occurro, etc. Tested on Pytorch 1.4-1.8. Sequence-to-video conversions require FFMPEG. For more explicit details refer to the original implementation.
What are some alternatives?
jukebox - Code for the paper "Jukebox: A Generative Model for Music"
AvatarMe - Public repository for the CVPR 2020 paper AvatarMe and the TPAMI 2021 AvatarMe++
simsiam-cifar10 - Code to train the SimSiam model on cifar10 using PyTorch
stargan2 - StarGAN2 for practice
dnn_from_scratch - A high level deep learning library for Convolutional Neural Networks,GANs and more, made from scratch(numpy/cupy implementation).
meshed-memory-transformer - Meshed-Memory Transformer for Image Captioning. CVPR 2020
generative-inpainting-pytorch - A PyTorch reimplementation for paper Generative Image Inpainting with Contextual Attention (https://arxiv.org/abs/1801.07892)
VIBE - Official implementation of CVPR2020 paper "VIBE: Video Inference for Human Body Pose and Shape Estimation"
lightweight-gan - Implementation of 'lightweight' GAN, proposed in ICLR 2021, in Pytorch. High resolution image generations that can be trained within a day or two
hand_object_detector - Project and dataset webpage:
denoising-diffusion-pytorch - Implementation of Denoising Diffusion Probabilistic Model in Pytorch
Stacked_DMSHN_bokeh - Official Repository for our CVPRW (MAI'21) paper.