Transfer-Learning-Library
StyleDomain
Transfer-Learning-Library | StyleDomain | |
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1 | 1 | |
3,150 | 23 | |
2.2% | - | |
6.9 | 6.4 | |
about 1 month ago | 4 months ago | |
Python | Python | |
MIT License | - |
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Transfer-Learning-Library
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[R] pytorch library for audio/speech domain adaptation?
Are there any pytorch libraries to do benchmarking of domain adaptation methods for audio/speech tasks? Something like the Transfer Learning Library (https://github.com/thuml/Transfer-Learning-Library/) for images.
StyleDomain
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[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.
What are some alternatives?
TranAD - [VLDB'22] Anomaly Detection using Transformers, self-conditioning and adversarial training.
MotionBERT - [ICCV 2023] PyTorch Implementation of "MotionBERT: A Unified Perspective on Learning Human Motion Representations"
DeepLabCut - Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans
transferlearning - Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
CEPC - A domain adaptation model
AdaTime - [TKDD 2023] AdaTime: A Benchmarking Suite for Domain Adaptation on Time Series Data
pytorch-adapt - Domain adaptation made easy. Fully featured, modular, and customizable.
DA-Faster-RCNN - Detectron2 implementation of DA-Faster R-CNN, Domain Adaptive Faster R-CNN for Object Detection in the Wild
AugMax - [NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Animashree Anandkumar, and Zhangyang Wang.