๐Ÿ“–
Latent Space Jam: Layout Guided Video Synthesis
Asaf Joseph, Moshe Mandel, Ohad Fried

Latent Space Jam: Layout Guided Video Synthesis

Author / Organization:
Science & Mathematics Published 2026 Verification Pending

Overview & Synopsis

Adding control to video generation often requires training, which demands additional computational resources, data, or architectural changes. We propose a training-free approach that utilizes pretrained video diffusion models to control object layout and motion using coarse layouts. Our method operates in two passes: first, it steers spatiotemporal placement through prompt-guided cross-attention to produce a coarse visual guide; second, this guide conditions the same model to generate a high-quality, layoutconsistent video. The approach enables coordinated motion with strong temporal consistency, supporting diverse trajectories and object interactions without additional training. Extensive experiments show that our method consistently outperforms prior work in overlap and trajectory accuracy, as well as visual quality across static, dynamic, and multi-object scene settings.

Indexed from repository: arXiv (arxiv.org)
Loading document from verified source...
Keyboard Shortcuts: ← / → for pages • + / - for zoom • 0 to fit width Powered by Mozilla PDF.js v3.11

Document Information

Document Title Latent Space Jam: Layout Guided Video Synthesis
Author / Organization Asaf Joseph, Moshe Mandel, Ohad Fried
Subject & Discipline cs.CV
Categories Science & Mathematics
Publication Year 2026
License / Rights arXiv Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website arXiv (arxiv.org)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-266098
Original Source Link Visit Source Page on arxiv.org »