vision-aided-gan
contrastive-unpaired-translation
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| vision-aided-gan | contrastive-unpaired-translation | |
|---|---|---|
| 3 | 6 | |
| 356 | 1,892 | |
| - | - | |
| 2.2 | 0.0 | |
| 9 months ago | 3 months ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 or later |
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vision-aided-gan
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[D] Is the GAN architecture currently old-fashioned?
If you are looking for more traditional noise -> xxx GANs, go for https://github.com/autonomousvision/projected_gan/. Another recent work is https://github.com/nupurkmr9/vision-aided-gan.
contrastive-unpaired-translation
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[D] What is current SOTA in Image to Image Translation?
For unpaired image-to-image translation, the SOTA is probably Contrastive Unpaired Translation, which is developed by the same group that developed CycleGAN and is kind of the successor algorithm.
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[P] Can't finish my master's thesis. What to do?
Are you using your synthetic 3D character views directly or do you use some kind of domain adaptation on them? It's been a while since I've worked with such techniques and it was more focused on semantic segmentation, so I can't tell you much about recent work in this area, but maybe you can find some inspiration here: https://paperswithcode.com/task/synthetic-to-real-translation You could for example try training something like CUT on an unpaired set of images from your 3D models and a set of real photos of soccer players, and then apply the synthetic-to-real model to your synthetic images to make them fit better into the distribution of real images.
Here is link number 1 - Previous text "CUT"
What are some alternatives?
pix2pixHD - Synthesizing and manipulating 2048x1024 images with conditional GANs
CycleGAN - Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.
pytorch-CycleGAN-and-pix2pix - Image-to-Image Translation in PyTorch
vrn - :man: Code for "Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression"
pytorch-AdaIN - Unofficial pytorch implementation of 'Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization' [Huang+, ICCV2017]
mmagic - OpenMMLab Multimodal Advanced, Generative, and Intelligent Creation Toolbox. Unlock the magic 🪄: Generative-AI (AIGC), easy-to-use APIs, awsome model zoo, diffusion models, image/video restoration/enhancement, etc.
cycle-gan-pytorch - This repository contains an implementation of the Cylce-GAN architecture for style transfer along with instructions to train on an own dataset.
cartoonize - A demo webapp to convert images and videos into cartoon!
sketchedit - SketchEdit: Mask-Free Local Image Manipulation with Partial Sketches, CVPR2022
PyTorch-GAN - PyTorch implementations of Generative Adversarial Networks.
pytorch-gans - PyTorch implementation of GANs (Generative Adversarial Networks). DCGAN, Pix2Pix, CycleGAN, SRGAN
StyleSwin - [CVPR 2022] StyleSwin: Transformer-based GAN for High-resolution Image Generation