VPA: Fully Test-Time Visual Prompt Adaptation-Reference-Cited by-同舟云学术

VPA: Fully Test-Time Visual Prompt Adaptation

Published:2023-10-26 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 31st ACM International Conference on Multimedia
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Author:

Sun Jiachen¹^ORCID,Ibrahim Mark²^ORCID,Hall Melissa²^ORCID,Evtimov Ivan³^ORCID,Mao Z. Morley¹^ORCID,Ferrer Cristian Canton³^ORCID,Hazirbas Caner²^ORCID

Affiliation:

1. University of Michigan, Ann Arbor, MI, USA

2. Meta AI, New York, NY, USA

3. Meta AI, Seattle, WA, USA

Funder

NSF (National Science Foundation)

National AI Institute for Edge Computing Leveraging Next Generation Wireless Networks

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3581783.3611835

Reference68 articles.

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3. Hyojin Bahng , Ali Jahanian , Swami Sankaranarayanan , and Phillip Isola . 2022. Exploring visual prompts for adapting large-scale models. arXiv preprint arXiv:2203.17274 , Vol. 1 , 3 ( 2022 ), 4. Hyojin Bahng, Ali Jahanian, Swami Sankaranarayanan, and Phillip Isola. 2022. Exploring visual prompts for adapting large-scale models. arXiv preprint arXiv:2203.17274, Vol. 1, 3 (2022), 4.

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5. Towards Evaluating the Robustness of Neural Networks