Meta-SelfLearning
Domain adaptation software
Develops a method to improve performance of computer vision tasks by adapting models to new domains and data sources through meta-learning and self-learning techniques.
Meta Self-learning for Multi-Source Domain Adaptation： A Benchmark
199 stars
3 watching
5 forks
Language: Python
last commit: over 2 years ago benchmarkcomputer-visiondatasetdomain-adaptationiccv2021meta-learningmulti-source-domain-adaptationocr-recognitionself-learningtext-recognition
Related projects:
| Repository | Description | Stars |
|---|---|---|
 naoto0804/cross-domain-detection | Develops object detection algorithms to adapt to new domains with limited supervision | 422 |
 wenkehuang/rethinkfl | Improves federated learning performance by incorporating domain knowledge and regularization to adapt models across diverse domains | 91 |
 chrisallenming/ltc-msda | An implementation of a knowledge aggregation method for adapting to multiple domains using a graph-based framework. | 68 |
 domainadaptation/salad | A toolbox for comparing and running domain adaptation algorithms on different datasets. | 333 |
 wasidennis/adaptsegnet | This project implements a deep learning-based approach to adapt semantic segmentation models from one domain to another. | 849 |
 easezyc/deep-transfer-learning | A collection of implementations of algorithms to adapt deep learning models from one domain to another | 892 |
 kaiyangzhou/dassl.pytorch | A PyTorch toolbox for supporting research and development of domain adaptation, generalization, and semi-supervised learning methods in computer vision. | 1,217 |
 baowenxuan/atp | An implementation of adaptive test-time personalization for federated learning in deep neural networks. | 16 |
 lhoyer/hrda | A framework for unsupervised domain adaptation in semantic segmentation using multi-resolution training and learned scale attention. | 235 |
 tristandeleu/pytorch-meta | Provides tools and datasets for meta-learning and few-shot learning in deep learning | 1,987 |
 layneh/self-adaptive-training | Improves deep network generalization under noise and enhances self-supervised representation learning | 127 |
 tsingz0/dbe | This implementation of a federated learning method aims to reduce domain bias in representation space, enabling more efficient knowledge transfer between clients and servers. | 22 |
 bupt-gamma/multi-component-graph-convolutional-collaborative-filtering | A deep learning framework for collaborative filtering and graph-based recommender systems | 60 |
 ikostrikov/pytorch-meta-optimizer | A PyTorch implementation of meta-learning using gradient descent to adapt to new tasks. | 312 |
 mop/bier | This project implements a deep metric learning framework using an adversarial auxiliary loss to improve robustness. | 39 |