Waffling around for Performance: Visual Classification with Random Words and Broad Concepts-Reference-Cited by-同舟云学术

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Waffling around for Performance: Visual Classification with Random Words and Broad Concepts

Published:2023-10-01 Issue: Volume: Page:15700-15711
ISSN:
Container-title:2023 IEEE/CVF International Conference on Computer Vision (ICCV)
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Author:

Roth Karsten¹,Kim Jae Myung¹,Sophia Koepke A.¹,Vinyals Oriol²,Schmid Cordelia³,Akata Zeynep¹

Affiliation:

1. University of Tübingen,Tübingen AI Center

2. Google DeepMind

3. PSL Research University,Inria, Ecole Normale Supérieure, CNRS

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10376473/10376477/10378352.pdf?arnumber=10378352

Reference68 articles.

1. Exploring visual prompts for adapting large-scale models;Bahng,2022

2. Leaving reality to imagination: Robust classification via generated datasets;Bansal,2023

3. Synthetic and natural noise both break neural machine translation;Belinkov;ICLR,2018

4. Food-101 – Mining Discriminative Components with Random Forests

5. Language models are few-shot learners;Brown;NeurIPS,2020

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Embracing Diversity: Interpretable Zero-shot Classification Beyond One Vector Per Class;The 2024 ACM Conference on Fairness, Accountability, and Transparency;2024-06-03

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