{"ID":3085643,"CreatedAt":"2026-06-05T06:46:15.197025399Z","UpdatedAt":"2026-06-05T12:00:18.729514559Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2605.27891","arxiv_id":"2605.27891","title":"SmartDirector: Keyframe-Conditioned Cinematic Video Generation with Narrative Pacing Control","abstract":"The narrative quality of a video fundamentally determines its perceptual value. Although existing video generation methods can produce visually appealing content, they predominantly rely on sparse conditioning signals such as text prompts or first/last frames, which limits precise control over narrative structure and temporal pacing. In this paper, we propose SmartDirector, a framework that enhances the narrative capacity of video generation models through multiple keyframes. SmartDirector supports flexible generation scenarios including single-shot generation, multi-shot narrative synthesis, and video extension. The framework operates in two stages: Director-Gen generates a low-resolution video conditioned on the provided keyframes, and Director-SR refines the output by exploiting high-resolution keyframes as semantic anchors to recover fine-grained details. To enable robust multi-keyframe training, we construct a data pipeline that curates single-shot and multi-shot sequences from movies. Extensive experiments demonstrate that SmartDirector substantially outperforms existing state-of-the-art approaches. We will release the code to facilitate further research.","short_abstract":"The narrative quality of a video fundamentally determines its perceptual value. Although existing video generation methods can produce visually appealing content, they predominantly rely on sparse conditioning signals such as text prompts or first/last frames, which limits precise control over narrative structure and t...","url_abs":"https://arxiv.org/abs/2605.27891","url_pdf":"https://arxiv.org/pdf/2605.27891v1","authors":"[\"Zhida Zhang\",\"Jie Ma\",\"Zhan Peng\",\"Haoxue Wu\",\"Yang Han\",\"Jun Liang\",\"Jie Cao\",\"Jing Li\"]","published":"2026-05-27T03:16:09Z","proceeding":"cs.CV","tasks":"[\"cs.CV\",\"cs.AI\"]","methods":"[]","has_code":false}