ChatGPT-Powered Hierarchical Comparisons for Image Classification
November 01, 2023 Β· Declared Dead Β· π Neural Information Processing Systems
"No code URL or promise found in abstract"
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Authors
Zhiyuan Ren, Yiyang Su, Xiaoming Liu
arXiv ID
2311.00206
Category
cs.CV: Computer Vision
Cross-listed
cs.AI
Citations
36
Venue
Neural Information Processing Systems
Last Checked
3 months ago
Abstract
The zero-shot open-vocabulary challenge in image classification is tackled by pretrained vision-language models like CLIP, which benefit from incorporating class-specific knowledge from large language models (LLMs) like ChatGPT. However, biases in CLIP lead to similar descriptions for distinct but related classes, prompting our novel image classification framework via hierarchical comparisons: using LLMs to recursively group classes into hierarchies and classifying images by comparing image-text embeddings at each hierarchy level, resulting in an intuitive, effective, and explainable approach.
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