Article Dans Une Revue IEEE Transactions on Multimedia Année : 2025

AesPrompt: Zero-shot Image Aesthetics Assessment with Multi-Granularity Aesthetic Prompt Learning

Résumé

Recent years have witnessed increasing interest towards image aesthetics assessment (IAA), which predicts the aesthetic appeal of images by simulating human perception. The state-of-the-art IAA methods, despite their significant advancements, typically rely heavily on time-consuming and laborintensive human annotation of aesthetic scores. Furthermore, they are subject to the generalization challenge, which is highly desired in real-world applications. Motivated by this, zero-shot image aesthetics assessment (ZIAA) is investigated to achieve robust model generalization without relying on manual aesthetic annotations, which remains largely underexplored. Specifically, a novel aesthetic prompt learning framework for ZIAA, dubbed AesPrompt, is presented in this paper. The key insight of AesPrompt is to emulate the human aesthetic perception process for learning aesthetic-oriented prompts in a multi-granularity manner. First, we first develop a new pseudo aesthetic distribution generation paradigm based on multi-LLM ensemble. Then, external knowledge of multi-granularity prompts encompassing image themes, emotions, and aesthetics is acquired. Through learning the multi-granularity aesthetic-oriented prompts, the proposed method achieves better generalization and interpretability. Extensive experiments on five IAA benchmarks demonstrate that AesPrompt consistently outperforms the state-of-the-art ZIAA methods across diverse-sourced images, covering natural images, artistic images, and artificial intelligence-generated images. The source code is available at https://github.com/sxfly99/AesPrompt.

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hal-05160413 , version 1 (14-07-2025)

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Xiangfei Sheng, Leida Li, Pengfei Chen, Li Cai, Giuseppe Valenzise. AesPrompt: Zero-shot Image Aesthetics Assessment with Multi-Granularity Aesthetic Prompt Learning. IEEE Transactions on Multimedia, 2025, pp.1-15. ⟨10.1109/TMM.2025.3632637⟩. ⟨hal-05160413⟩
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