SpriteStage：渐进式场景编程生成长篇动画

引擎再编排环节将草稿映射到生产资产和引擎能力，保留事件、几何与时间信息。三个完整动画时长约 9.

9 至 14.3 分钟，验证了框架生成长叙事的能力。

SpriteStage: Long Horizon Animation Generation via Progressive Scene Programming and Replay

Video generation models synthesize visual sequences from text and image inputs. Extending video generation to long animations requires actions, dialogue, camera coverage, and narrative developments to remain coordinated across scenes. Executable scene programs make these decisions available for inspection. Constructing an entire story before observing its execution can leave later scenes dependent on unrealized events. We present SpriteStage, a progressive scene programming framework that builds animation through iterative enactment and engine reorchestration. Iterative enactment generates each scene from an accepted world checkpoint and narrative snapshot, executes it on a shared spatial stage, and uses runtime and visual feedback to revise the relevant actions or story beats. The accepted outcome becomes the starting state for the next scene. Engine reorchestration maps the resulting draft to production assets and engine capabilities while retaining its events, geometry, and timing. Inspection of the assembled sequence and frozen replay carry the accepted performance into the final video. Three complete animations, ranging from approximately 9.9 to 14.3 minutes, demonstrate the framework's effectiveness in producing extended narratives through scene programming and engine execution.

This report is categorized under AITOP's "Papers" desk, focusing on US frontier AI labs and Silicon Valley technology leaders. Within our cross-regional analytical framework, it directly maps to AI developer toolchains, coding agents, and engineering workflows. Key entities and technical topics under continuous tracking include SpriteStage, 视频生成, 场景编程, 动画生成.

Source attribution: curated from arXiv cs.AI (@Zhaoqi Wang, Zijian Zhang, Jiamou Liu).