I2MVFormer: Large Language Model Generated Multi-View Document Supervision for Zero-Shot Image Classification-Reference-Cited by-同舟云学术

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I2MVFormer: Large Language Model Generated Multi-View Document Supervision for Zero-Shot Image Classification

Published:2023-06 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Author:

Naeem Muhammad Ferjad¹,Ali Khan Muhammad Gul Zain²,Xian Yongqin³,Afzal Muhammad Zeshan²,Stricker Didier²,Van Gool Luc¹,Tombari Federico⁴

Affiliation:

1. ETH Zürich

2. TUKL

3. Google

4. TUM

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10203037/10203050/10204007.pdf?arnumber=10204007

Reference69 articles.

1. An image is worth 16x16 words: Transformers for image recognition at scale;dosovitskiy;ICLRE,0

2. FILIP: Fine-grained interactive language-image pre-training;yao;ICLRE,0

3. Palm: Scaling language modeling with pathways;chowdhery;ArXiv Preprint,2022

4. Wikipedia2Vec: An Efficient Toolkit for Learning and Visualizing the Embeddings of Words and Entities from Wikipedia

5. Link the Head to the "Beak": Zero Shot Learning from Noisy Text Description at Part Precision

Cited by 3 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. Zero-Shot Action Recognition with ChatGPT-Based Instruction;Communications in Computer and Information Science;2023-10-30

2. Enhancing CLIP with GPT-4: Harnessing Visual Descriptions as Prompts;2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW);2023-10-02

3. Dynamic visual-guided selection for zero-shot learning;The Journal of Supercomputing;2023-09-13

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