pytorch implementation for Contrastive Adaptation Network
Pytorch implementation of four neural network based domain adaptation techniques: DeepCORAL, DDC, CDAN and CDAN+E. Evaluated on benchmark dataset Office31.
[CVPR 2020] Differential Treatment for Stuff and Things: A Simple Unsupervised Domain Adaptation Method for Semantic Segmentation
Unsupervised Domain Adaptation through Self-Supervision
Implement of the Rare-Class Enhancing and Prototype-Guided Patch-Wise Masking for Unsupervised Domain Adaptation
Unsupervised Domain Adaptation by Backpropagation
Unsupervised Domain Adaptation for Computer Vision Tasks
A PyTorch implementation for Unsupervised Domain Adaptation by Backpropagation
Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation. In CVPR 2019.
Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling
Tensorflow codes for ICML2018, Learning Semantic Representations for Unsupervised Domain Adaptation
Implementation of paper "Maximum Classifier Discrepancy for Unsupervised Domain Adaptation".
Auto-labeling of point cloud sequences for 3D object detection using an ensemble of experts and temporal refinement
Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization
翻译 - 转移学习图书馆
Code for paper "Unsupervised Domain Adaptation using Feature-Whitening and Consensus Loss" (CVPR 2019)
(ICRA 2023) Viewer-Centred Surface Completion for Unsupervised Domain Adaptation in 3D Object Detection