Unsupervised Domain Adaptation

281 papers with code • 16 benchmarks • 18 datasets

Unsupervised Domain Adaptation is a learning framework to transfer knowledge learned from source domains with a large number of annotated training examples to target domains with unlabeled data only.

Source: Domain-Specific Batch Normalization for Unsupervised Domain Adaptation

Greatest papers with code

Adversarial Discriminative Domain Adaptation

corenel/pytorch-adda CVPR 2017

Adversarial learning methods are a promising approach to training robust deep networks, and can generate complex samples across diverse domains.

General Classification Object Classification +2

Correlation Alignment for Unsupervised Domain Adaptation

eridgd/WCT-TF 6 Dec 2016

In contrast to subspace manifold methods, it aligns the original feature distributions of the source and target domains, rather than the bases of lower-dimensional subspaces.

Unsupervised Domain Adaptation

A DIRT-T Approach to Unsupervised Domain Adaptation

domainadaptation/salad ICLR 2018

Domain adaptation refers to the problem of leveraging labeled data in a source domain to learn an accurate model in a target domain where labels are scarce or unavailable.

Unsupervised Domain Adaptation

Domain Adaptive Faster R-CNN for Object Detection in the Wild

yuhuayc/da-faster-rcnn CVPR 2018

The results demonstrate the effectiveness of our proposed approach for robust object detection in various domain shift scenarios.

Region Proposal Robust Object Detection +1

Learning to cluster in order to transfer across domains and tasks


The key insight is that, in addition to features, we can transfer similarity information and this is sufficient to learn a similarity function and clustering network to perform both domain adaptation and cross-task transfer learning.

Transfer Learning Unsupervised Domain Adaptation

Rectifying Pseudo Label Learning via Uncertainty Estimation for Domain Adaptive Semantic Segmentation

layumi/Seg-Uncertainty 8 Mar 2020

This paper focuses on the unsupervised domain adaptation of transferring the knowledge from the source domain to the target domain in the context of semantic segmentation.

Synthetic-to-Real Translation Unsupervised Domain Adaptation +1