WATT: Weight Average Test-Time Adaptation of CLIP

Vision-Language Models (VLMs) such as CLIP have yielded unprecedented performance for zero-shot image classification, yet their generalization capability may still be seriously challenged when confronted to domain shifts. In response, we present Weight Average Test-Time Adaptation (WATT) of CLIP, a...

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Veröffentlicht in:	arXiv.org 2024-06
Hauptverfasser:	Osowiechi, David, Noori, Mehrdad, Vargas Hakim, Gustavo Adolfo, Yazdanpanah, Moslem, Bahri, Ali, Cheraghalikhani, Milad, Dastani, Sahar, Beizaee, Farzad, Ismail Ben Ayed, Desrosiers, Christian
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation Datasets Image classification Performance enhancement Testing time
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