A planner-orchestrator system learns long-horizon image editing by maximizing outcome-based rewards from a vision-language judge and refining plans from successful trajectories.
arXiv preprint arXiv:2508.06916 (2025)
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CAMEO uses coordinated agents for planning, prompting, generation, and quality feedback to achieve higher structural reliability in conditional image editing than single-step models.
citing papers explorer
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From Plans to Pixels: Learning to Plan and Orchestrate for Open-Ended Image Editing
A planner-orchestrator system learns long-horizon image editing by maximizing outcome-based rewards from a vision-language judge and refining plans from successful trajectories.
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CAMEO: A Conditional and Quality-Aware Multi-Agent Image Editing Orchestrator
CAMEO uses coordinated agents for planning, prompting, generation, and quality feedback to achieve higher structural reliability in conditional image editing than single-step models.