CoAgent: A Framework for Coherent Video Generation
Analysis
This paper addresses a critical problem in text-to-video generation: maintaining narrative coherence and visual consistency. The proposed CoAgent framework offers a structured approach to tackle these issues, moving beyond independent shot generation. The plan-synthesize-verify pipeline, incorporating a Storyboard Planner, Global Context Manager, Visual Consistency Controller, and Verifier Agent, is a promising approach to improve the quality of long-form video generation. The focus on entity-level memory and selective regeneration is particularly noteworthy.
Key Takeaways
- •CoAgent is a collaborative and closed-loop framework for coherent video generation.
- •It uses a plan-synthesize-verify pipeline.
- •Key components include a Storyboard Planner, Global Context Manager, Visual Consistency Controller, and Verifier Agent.
- •The framework aims to address identity drift, scene inconsistency, and unstable temporal structure in video generation.
Reference
“CoAgent significantly improves coherence, visual consistency, and narrative quality in long-form video generation.”