StyleDomain
anycost-gan
| StyleDomain | anycost-gan | |
|---|---|---|
| 1 | 1 | |
| 23 | 769 | |
| - | 0.3% | |
| 6.4 | 2.5 | |
| 5 months ago | 7 months ago | |
| Python | Python | |
| - | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
StyleDomain
-
[Research] Exciting New Paper on StyleGAN Domain Adaptation: StyleDomain - ICCV 2023
Abstract: Domain adaptation of GANs is a problem of fine-tuning GAN models pretrained on a large dataset (e.g., StyleGAN) to a specific domain with few samples (e.g., painting faces, sketches, etc.). While there are many methods that tackle this problem in different ways, there are still many important questions that remain unanswered. In this paper, we provide a systematic and in-depth analysis of the domain adaptation problem of GANs, focusing on the StyleGAN model. We perform a detailed exploration of the most important parts of StyleGAN that are responsible for adapting the generator to a new domain depending on the similarity between the source and target domains. As a result of this study, we propose new efficient and lightweight parameterizations of StyleGAN for domain adaptation. Particularly, we show that there exist directions in StyleSpace (StyleDomain directions) that are sufficient for adapting to similar domains. For dissimilar domains, we propose Affine+ and AffineLight+ parameterizations that allow us to outperform existing baselines in few-shot adaptation while having significantly fewer training parameters. Finally, we examine StyleDomain directions and discover their many surprising properties that we apply for domain mixing and cross-domain image morphing. Source code can be found at GitHub.
anycost-gan
What are some alternatives?
Transfer-Learning-Library - Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization
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
MotionBERT - [ICCV 2023] PyTorch Implementation of "MotionBERT: A Unified Perspective on Learning Human Motion Representations"
pytorch-CycleGAN-and-pix2pix - Image-to-Image Translation in PyTorch
PaddleGAN - PaddlePaddle GAN library, including lots of interesting applications like First-Order motion transfer, Wav2Lip, picture repair, image editing, photo2cartoon, image style transfer, GPEN, and so on.
Anime-face-generation-DCGAN-webapp - A port of my Anime face generation using Pytorch into a Webapp
stylegan-waifu-generator - Generate your waifu with styleGAN, stylegan老婆生成器
DeepSIM - Official PyTorch implementation of the paper: "DeepSIM: Image Shape Manipulation from a Single Augmented Training Sample" (ICCV 2021 Oral)
the-gan-zoo - A list of all named GANs!
CycleGAN - Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.
alias-free-gan-pytorch - Unofficial implementation of Alias-Free Generative Adversarial Networks. (https://arxiv.org/abs/2106.12423) in PyTorch
GIMP-ML - AI for GNU Image Manipulation Program