CANVAS: Continuity-Aware Narratives via Visual Agentic Storyboarding

2026-04-15

AI Summary

This work addresses the challenge of visual incoherence in long-form visual storytelling, which often manifests as abrupt character appearance changes, inconsistent backgrounds, and disjointed scene transitions. To tackle this, the authors propose a multi-agent collaborative framework that explicitly models visual continuity across multiple shots for the first time, enforcing consistency through character continuity constraints, persistent background anchors, and position-aware scene planning. The study introduces HardContinuityBench, a new benchmark for evaluating long-range visual consistency, and demonstrates significant performance gains over existing methods on ST-Bench and ViStoryBench, achieving relative improvements of 21.6% in background continuity, 9.6% in character consistency, and 7.6% in prop consistency.

Technology Category

• Computer Vision: Visual Reasoning & Symbolic Representations
• Multiagent Systems: Multiagent Planning
• Humans and AI: Human-Aware Planning and Behavior Prediction

Application Category

• Economics, Online Markets and Human Computation: LLM based quality controls for crowd work
• Responsible Web: Consent frameworks and practices on the web
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs

Abstract

Long-form visual storytelling requires maintaining continuity across shots, including consistent characters, stable environments, and smooth scene transitions. While existing generative models can produce strong individual frames, they fail to preserve such continuity, leading to appearance changes, inconsistent backgrounds, and abrupt scene shifts. We introduce CANVAS (Continuity-Aware Narratives via Visual Agentic Storyboarding), a multi-agent framework that explicitly plans visual continuity in multi-shot narratives. CANVAS enforces coherence through character continuity, persistent background anchors, and location-aware scene planning for smooth transitions within the same setting We evaluate CANVAS on two storyboard generation benchmarks ST-BENCH and ViStoryBench and introduce a new challenging benchmark HardContinuityBench for long-range narrative consistency. CANVAS consistently outperforms the best-performing baseline, improving background continuity by 21.6%, character consistency by 9.6% and props consistency by 7.6%.

Problem

• visual storytelling
• continuity
• character consistency
• background stability
• scene transitions

Innovation

• visual storytelling
• continuity-aware
• multi-agent framework
• storyboard generation
• narrative consistency