JarvisArt/MMArt-Bench
JarvisArt: Liberating Human Artistic Creativity via an Intelligent Photo Retouching Agent. 🌍 Introduction MMArt-Bench. To provide a comprehensive evaluation of JarvisArt’s performance, we introduce the MMArt-Bench, which is sampled from the MMArt dataset. It includes four main scenarios: portrait, landscape, street scenes, and still life, with 50 instances per category, totaling 200 instances. Each primary category contains multiple subcategories. For region-level evaluation… See the full description on the dataset page: https://huggingface.co/datasets/JarvisArt/MMArt-Bench.
JarvisArt: Liberating Human Artistic Creativity via an Intelligent Photo Retouching Agent.
🌍 Introduction
MMArt-Bench. To provide a comprehensive evaluation of JarvisArt’s performance, we introduce the MMArt-Bench, which is sampled from the MMArt dataset. It includes four main scenarios: portrait, landscape, street scenes, and still life, with 50 instances per category, totaling 200 instances. Each primary category contains multiple subcategories. For region-level evaluation, we utilize a portrait subset comprising 50 human-centered images with mask annotations.
📜 Citation
If you find our paper and code useful in your research, please consider giving a star ⭐ and citation 📝.
@article{jarvisart2025,
title={JarvisArt: Liberating Human Artistic Creativity via an Intelligent Photo Retouching Agent},
author={Yunlong Lin and Zixu Lin and Kunjie Lin and Jinbin Bai and Panwang Pan and Chenxin Li and Haoyu Chen and Zhongdao Wang and Xinghao Ding and Wenbo Li and Shuicheng Yan},
year={2025},
journal={arXiv preprint arXiv:2506.17612}
}