Aug. 17, 2022, 1:12 a.m. | Robert A. Marsden, Mario Döbler, Bin Yang

cs.CV updates on arXiv.org arxiv.org

Domain shifts at test-time are inevitable in practice. Test-time adaptation
addresses this problem by adapting the model during deployment. Recent work
theoretically showed that self-training can be a strong method in the setting
of gradual domain shifts. In this work we show the natural connection between
gradual domain adaptation and test-time adaptation. We publish a new synthetic
dataset called CarlaTTA that allows to explore gradual domain shifts during
test-time and evaluate several methods in the area of unsupervised domain
adaptation …

arxiv cv self-training style transfer test time training transfer

Data Scientist (m/f/x/d)

@ Symanto Research GmbH & Co. KG | Spain, Germany

AI Scientist/Engineer

@ OKX | Singapore

Research Engineering/ Scientist Associate I

@ The University of Texas at Austin | AUSTIN, TX

Senior Data Engineer

@ Algolia | London, England

Fundamental Equities - Vice President, Equity Quant Research Analyst (Income & Value Investment Team)

@ BlackRock | NY7 - 50 Hudson Yards, New York

Snowflake Data Analytics

@ Devoteam | Madrid, Spain