3 papers
cs.CV2026
MMArt: A Multi-Perspective Multimodal Dataset for Visual Art Understanding
Shuai Wang, Wangyuan Ding, Yixian Shen +5
Recent vision-language models demonstrate impressive general visual understanding, yet their art interpretation remains shallow: they describe surface content but struggle with for…
cs.AI2026
A-MAR: Agent-based Multimodal Art Retrieval for Fine-Grained Artwork Understanding
Shuai Wang, Hongyi Zhu, Jia-Hong Huang +6
Understanding artworks requires multi-step reasoning over visual content and cultural, historical, and stylistic context. While recent multimodal large language models show promise…
cs.AI2025
ArtRAG: Retrieval-Augmented Generation with Structured Context for Visual Art Understanding
Shuai Wang, Ivona Najdenkoska, Hongyi Zhu +4
Understanding visual art requires reasoning across multiple perspectives -- cultural, historical, and stylistic -- beyond mere object recognition. While recent multimodal large lan…