Parameter-free Online Test-time Adaptation

Training state-of-the-art vision models has become prohibitively expensive for researchers and practitioners. For the sake of accessibility and resource reuse, it is important to focus on adapting these models to a variety of down-stream scenarios. An interesting and practical paradigm is online tes...

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Vydané v:	Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) s. 8334 - 8343
Hlavní autori:	Boudiaf, Malik, Mueller, Romain, Ayed, Ismail Ben, Bertinetto, Luca
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.06.2022
Predmet:	Adaptation models Laplace equations Maximum likelihood estimation Memory management Protocols Self-& semi-& meta- Efficient learning and inferences; Transfer/low-shot/long-tail learning Training Uncertainty
ISSN:	1063-6919
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