DramaDirector: Geometry-Guided Short Drama Generation

• URL: http://arxiv.org/abs/2606.24107v1
• Date: Tue, 23 Jun 2026 03:50:28 GMT
• Title: DramaDirector: Geometry-Guided Short Drama Generation
• Abstract summary: We study plot-to-short-drama generation, where a global plot and local context are transformed into visually grounded multi-shot videos.<n>We propose DramaDirector, a geometry-grounded framework that lets the planner borrow cinematographic geometry from a gallery of real short-drama shots.<n>We also introduce DramaBoard, a benchmark built from 35 live-action dramas, 2.8K episodes, and 81K shots.
• Score: 51.430988173490384
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Short dramas, with their rapid shot rhythms, dialogue-driven focus shifts, and demanding cinematographic grounding, pose challenges that prompt-level or text-only video generation pipelines struggle to meet. We study plot-to-short-drama generation, where a global plot and local context are transformed into visually grounded multi-shot videos. We propose DramaDirector, a geometry-grounded framework that lets the planner borrow cinematographic geometry from a gallery of real short-drama shots indexed by depth and pose. DramaDirector decouples each shot into static visual and dynamic narrative conditions, trains the planner with schema-constrained SFT and GRPO under a learned text-visual alignment reward, and retrieves depth-pose references to guide first-frame generation and image-to-video synthesis. We also introduce DramaBoard, a benchmark built from 35 live-action dramas, 2.8K episodes, and 81K shots, with structured storyboards and multi-dimensional evaluation protocols. Experiments show that DramaDirector improves over representative multi-agent and video generation baselines on faithfulness, consistency, and controllability. Our code is released at: https://github.com/iLearn-Lab/DramaDirector

Related papers

• PAI-Actor: Cinematic Multi-Character Replacement in Dynamic Scenes [51.8637101384136]
  We present PAI-Actor, a cinematic multi-character animation framework for character replacement in dynamic movie scenes.<n>Our goal is to replace and animate multiple characters within real video clips while preserving the original scene dynamics, camera motion, and background content.<n>Experiments show that PAI-Actor enables high-fidelity multi-character animation with strong scene consistency, cinematic visual quality, and efficient long-form generation.
  arXiv  Detail & Related papers  (2026-09-05T06:27:27Z)
• CinemaTraj: Composing Atomic Camera Trajectories for 3D Scenes with LLM Agents [14.879115975370842]
  CinemaTraj is a framework that reframes camera trajectory planning as a language-grounded spatial reasoning problem.<n>It produces prompt-faithful, collision-free trajectories with high cinematographic quality.
  arXiv  Detail & Related papers  (2026-07-29T13:41:52Z)
• One Sentence, One Drama: Personalized Short-Form Drama Generation via Multi-Agent Systems [17.754369892506542]
  One Sentence, One Drama is a hierarchical multi-agent framework that transforms a user's single-sentence idea into a fully produced short drama.<n>Our approach is built upon three key components: (1) a multi-agent debate-based story generation module that enforces short-drama pacing and narrative coherence; (2) a 3D-grounded first-frame generation mechanism that establishes a shared spatial reference for consistent character positioning and scene layout across clips; and (3) multi-stage reviewer loops that perform comprehensive error detection and targeted revision across script, visual, and video generation stages.
  arXiv  Detail & Related papers  (2026-05-21T08:15:46Z)
• Soap2Soap: Long Cinematic Video Remaking via Multi-Agent Collaboration [61.98029663481308]
  Soap2Soap is a multi-agent framework that enforces long-term visual consistency through a DualBridge mechanism.<n>A closed-loop verification agent audits identity, stability, and alignment to trigger selective regeneration.
  arXiv  Detail & Related papers  (2026-05-17T12:38:21Z)
• Captain Cinema: Towards Short Movie Generation [66.22442526026215]
  We present Captain Cinema, a generation framework for short movie generation.<n>Our approach generates a sequence of synthesiss that outline the entire narrative.<n>Our model is trained on a specially curated dataset consisting of interleaved data pairs.
  arXiv  Detail & Related papers  (2025-07-24T17:59:56Z)
• CineVerse: Consistent Keyframe Synthesis for Cinematic Scene Composition [23.795982778641573]
  We present CineVerse, a novel framework for the task of cinematic scene composition.<n>Similar to traditional multi-shot generation, our task emphasizes the need for consistency and continuity across frames.<n>Our task also focuses on addressing challenges inherent to filmmaking, such as multiple characters, complex interactions, and visual cinematic effects.
  arXiv  Detail & Related papers  (2025-04-28T15:28:14Z)
• Total-Recon: Deformable Scene Reconstruction for Embodied View Synthesis [76.72505510632904]
  We present Total-Recon, the first method to reconstruct deformable scenes from long monocular RGBD videos. Our method hierarchically decomposes the scene into the background and objects, whose motion is decomposed into root-body motion and local articulations.
  arXiv  Detail & Related papers  (2023-04-24T17:59:52Z)
• A Local-to-Global Approach to Multi-modal Movie Scene Segmentation [95.34033481442353]
  We build a large-scale video dataset MovieScenes, which contains 21K annotated scene segments from 150 movies. We propose a local-to-global scene segmentation framework, which integrates multi-modal information across three levels, i.e. clip, segment, and movie. Our experiments show that the proposed network is able to segment a movie into scenes with high accuracy, consistently outperforming previous methods.
  arXiv  Detail & Related papers  (2020-04-06T13:58:08Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.