An Empirical Analysis of GPT-4V's Performance on Fashion Aesthetic Evaluation
Fashion aesthetic evaluation is the task of estimating how well the outfits worn by individuals in images suit them.In this work, we examine the zero-shot performance of GPT-4V on this task for the first time.We show that its predictions align fairly well with human judgments on our datasets, and also find that it struggles with ranking outfits in similar colors.The code is available at https://github.com/st-tech/gpt4v-fashion-aesthetic-evaluation.
Authors
- Ryotaro Shimizu
- Takashi Wada
- Takuya Furusawa (ORCID: https://orcid.org/0000-0001-9521-6514)
- Yuki Saito (ORCID: https://orcid.org/0000-0003-0492-414X)
- Yuki Hirakawa
- Sai Htaung Kham
- Kazuya Morishita
Publication Details
- Published
- 2024-11-19
- DOI
- https://doi.org/10.1145/3681758.3698022
- Citations
- 4
- Primary Topic
- Consumer Perception and Purchasing Behavior
- Type
- article
- Field-Weighted Citation Impact
- 1.76