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arXiv · 2311.00206

ChatGPT-Powered Hierarchical Comparisons for Image Classification

Zhiyuan Ren·Yiyang Su·Xiaoming Liu
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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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Zhiyuan Ren, Yiyang Su, Xiaoming Liu. 2023-11-01. ChatGPT-Powered Hierarchical Comparisons for Image Classification. https://arxiv.org/abs/2311.00206

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