unsupervised-domain-adaptation

Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization

[CVPR22] Official Implementation of DAFormer: Improving Network Architectures and Training Strategies for Domain-Adaptive Semantic Segmentation

Semantic Segmentation for Remote Sensing

[ICLR-2020] Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification.

PyTorch open-source toolbox for unsupervised or domain adaptive object re-ID.

pytorch implementation for Contrastive Adaptation Network

[ECCV22] Official Implementation of HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation

[TKDD 2023] AdaTime: A Benchmarking Suite for Domain Adaptation on Time Series Data

Implementation of ECCV 2020 paper "Every Pixel Matters: Center-aware Feature Alignment for Domain Adaptive Object Detector"

Self-supervised Augmentation Consistency for Adapting Semantic Segmentation (CVPR 2021)

NeurIPS 2023: Towards Generic Semi-Supervised Framework for Volumetric Medical Image Segmentation

Code for ICML2020 "Implicit Class-Conditioned Domain Alignment for Unsupervised Domain Adaptation"

An official implementation of ICML 2022 paper "Learning Domain Adaptive Object Detection with Probabilistic Teacher"."

Cross-Domain Car Detection Using Unsupervised Image-to-Image Translation: From Day to Night

[AAAI 2024] Prompt-based Distribution Alignment for Unsupervised Domain Adaptation

Deep learning research implemented on notebooks using PyTorch.

Official Detectron2 implementation of DA-RetinaNet, An unsupervised domain adaptation scheme for single-stage artwork recognition in cultural sites, Image and Vision Computing (IMAVIS) 2021

Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling

Official implementation of "Align and Distill: Unifying and Improving Domain Adaptive Object Detection" (TMLR 2025)

This is a PyTorch implementation of the Unsupervised Domain Adaptation method proposed in the paper Deep CORAL: Correlation Alignment for Deep Domain Adaptation. Baochen Sun and Kate Saenko (ECCV 2016).