source-free-domain-adaptation topic

code released for our ICML 2020 paper "Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation"

tim-learn

code for our TPAMI 2021 paper "Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer"

tim-learn

code for our ICCV 2021 paper 'Generalized Source-free Domain Adaptation'

Albert0147

Code for our NeurIPS 2022 (spotlight) paper 'Attracting and Dispersing: A Simple Approach for Source-free Domain Adaptation'

Albert0147

Unsupervised Domain Adaptation without Source Data by Casting a BAIT

Albert0147

Code for our NeurIPS 2021 paper 'Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation'

Albert0147

[CVPR 2022 Oral] Towards Fewer Annotations: Active Learning via Region Impurity and Prediction Uncertainty for Domain Adaptive Semantic Segmentation https://arxiv.org/abs/2111.12940

BIT-DA

code for our CVPR 2022 paper "DINE: Domain Adaptation from Single and Multiple Black-box Predictors"

tim-learn

[ECCV22] Concurrent Subsidiary Supervision for Unsupervised Source-Free Domain Adaptation

val-iisc

Collection of awesome test-time (domain/batch/instance) adaptation methods

tim-learn