CREA: A Collaborative Multi-Agent Framework for Creative Image Editing and Generation
Kavana Venkatesh, Connor Dunlop, Pinar Yanardag
Abstract
Creativity in AI imagery remains a fundamental challenge, requiring not only the generation of visually compelling content but also the capacity to add novel, expressive, and artistically rich transformations to images. Unlike conventional editing tasks that rely on direct prompt-based modifications, creative image editing requires an autonomous, iterative approach that balances originality, coherence, and artistic intent. To address this, we introduce CREA, a novel multi-agent collaborative framework that mimics the human creative process. Our framework leverages a team of specialized AI agents who dynamically collaborate to conceptualize, generate, critique, and enhance images. Through extensive qualitative and quantitative evaluations, we demonstrate that CREA significantly outperforms state-of-the-art methods in diversity, semantic alignment, and creative transformation. To the best of our knowledge, this is the first work to introduce the task of creative editing.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 57244c63-23f2-441d-bc92-c3c973f50c33Cited by top-tier papers2
- CREward: A Type-Specific Creativity Reward ModelJiyeon Han, Ali Mahdavi-Amiri, Hao Zhang, Haedong JeongCVPR 2026
- OrchJail: Jailbreaking Tool-Calling Text-to-Image Agents by Orchestration-Guided FuzzingJianming Chen, Yawen Wang, Junjie Wang, Zhe Liu et al.ICML 2026
Builds on23
- Denoising Diffusion Probabilistic ModelsJonathan Ho, Ajay Jain, Pieter AbbeelNeurIPS 2020 · 35,902 citations
- Chain-of-Thought Prompting Elicits Reasoning in Large Language ModelsJason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma et al.NeurIPS 2022 · 22,562 citations
- High-Resolution Image Synthesis with Latent Diffusion ModelsRobin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser et al.CVPR 2022 · 13,123 citations
- Photorealistic Text-to-Image Diffusion Models with Deep Language UnderstandingChitwan Saharia, William Chan, Saurabh Saxena, Lala Li et al.NeurIPS 2022 · 8,965 citations
- Adding Conditional Control to Text-to-Image Diffusion ModelsLvmin Zhang, Anyi Rao, Maneesh AgrawalaICCV 2023 · 6,759 citations
Related papers
- ContextCam: Bridging Context Awareness with Creative Human-AI Image Co-CreationXianzhe Fan, Zihan Wu, Chun Yu, Fenggui Rao et al.CHI 2024 · 49 citations
- Multi-Agent Amodal Completion: Direct Synthesis with Fine-Grained Semantic GuidanceHongxing Fan, Lipeng Wang, Haohua Chen, Zehuan Huang et al.ACM MM 2025 · 3 citations
- Creation-Mmbench: Assessing Context-Aware Creative Intelligence in MllmsXinyu Fang, Zhijian Chen, Kai Lan, Lixin Ma et al.ICCV 2025 · 23 citations
- Talk2Image: A Multi-Agent System for Multi-Turn Image Generation and EditingShichao Ma, Yunhe Guo, Jiahao Su, Qihe Huang et al.AAAI 2026 · 9 citations
- Understanding Nonlinear Collaboration between Human and AI Agents: A Co-design Framework for Creative DesignJiayi Zhou, Renzhong Li, Junxiu Tang, Tan Tang et al.CHI 2024 · 100 citations
