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

GT-RIPL/L2C ICLR 2018

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