arXiv (All)
open access
Multi-Grid Post-Training for Long-Form Multi-Shot Video Generation
Generating long-form multi-shot videos requires coherent within-shot motion and visually consistent narratives across shots. Existing video generators favor continuous motion and struggle to present complete shot sets when an entire narrative is packed along one temporal axis. We propose MovieGrid,
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Temporal State Transport in Video Generation: Diagnosing and Correcting Spectral Imbalance#985854
- PersonaShot: Benchmarking Person-Centric Narrative Continuity in Multi-Shot Video Generation#625278
- PersonaShot: Benchmarking Person-Centric Narrative Continuity in Multi-Shot Video Generation#623005
- Camera Artist: A Multi-Agent Framework for Cinematic Language Storytelling Video Generation#6024
- One Editor, Many Edits: A Unified Training-Free Framework for Diverse Video Editing#639700
Record · ID 973954
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive