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DrawVideo introduces a novel framework that enables precise control over long-form video generation using sketch-based storyboards, addressing key limitations in pose and camera composition found in standard text-to-video models. By generating structure-aligned reference keyframes before synthesizing intermediate clips, the system achieves high fidelity in spatial layout and motion consistency for director-oriented workflows. This advancement represents a significant step forward in controllable generative video synthesis within artificial intelligence research.
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DrawVideo: Grounded and Faithful Multi-Shot Video Generation from Storyboard Keyframe Sketches

arXiv2 min read

arXiv:2605.23508v2 Announce Type: replace-cross Abstract: Long video generation requires high-fidelity visual synthesis, coherent narrative organization, shot-level structure, and explicit user control. Existing text-to-video methods typically generate videos from a single long-form prompt, making it difficult for creators to directly control character pose, camera composition, spatial layout, and local motion. We propose DrawVideo, a sketch-guided and storyboard-driven framework that grounds multi-shot video generation in creator-provided spatial structure, appearance, and motion. Each shot is specified by a black-and-white sketch, an appearance prompt, and a motion prompt. DrawVideo first generates a structure-aligned reference keyframe, expands the motion description into derivative keyframes representing ordered action states, and then synthesizes local video clips between adjacent keyframes. We further introduce SketchLongVideo, to the best of our knowledge the first evaluation dataset of ordered multi-shot storyboards with aligned sketch, appearance, and motion conditions. Extensive experiments demonstrate strong structural controllability, appearance consistency, intra-shot visual stability, and motion alignment, providing an effective solution for director-oriented video creation.

Abstract:Long video generation requires high-fidelity visual synthesis, coherent narrative organization, shot-level structure, and explicit user control. Existing text-to-video methods typically generate videos from a single long-form prompt, making it difficult for creators to directly control character pose, camera composition, spatial layout, and local motion. We propose DrawVideo, a sketch-guided and storyboard-driven framework that grounds multi-shot video generation in creator-provided spatial structure, appearance, and motion. Each shot is specified by a black-and-white sketch, an appearance prompt, and a motion prompt. DrawVideo first generates a structure-aligned reference keyframe, expands the motion description into derivative keyframes representing ordered action states, and then synthesizes local video clips between adjacent keyframes. We further introduce SketchLongVideo, to the best of our knowledge the first evaluation dataset of ordered multi-shot storyboards with aligned sketch, appearance, and motion conditions. Extensive experiments demonstrate strong structural controllability, appearance consistency, intra-shot visual stability, and motion alignment, providing an effective solution for director-oriented video creation.

Graphics (cs.GR); Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV); Multimedia (cs.MM); Image and Video Processing (eess.IV)

arXiv:2605.23508 [cs.GR]

(or arXiv:2605.23508v2 [cs.GR] for this version)

Full text under the publisher's open licence · 179 words

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