English

When and Where do Events Switch in Multi-Event Video Generation?

Computer Vision and Pattern Recognition 2025-10-06 v1 Artificial Intelligence

Abstract

Text-to-video (T2V) generation has surged in response to challenging questions, especially when a long video must depict multiple sequential events with temporal coherence and controllable content. Existing methods that extend to multi-event generation omit an inspection of the intrinsic factor in event shifting. The paper aims to answer the central question: When and where multi-event prompts control event transition during T2V generation. This work introduces MEve, a self-curated prompt suite for evaluating multi-event text-to-video (T2V) generation, and conducts a systematic study of two representative model families, i.e., OpenSora and CogVideoX. Extensive experiments demonstrate the importance of early intervention in denoising steps and block-wise model layers, revealing the essential factor for multi-event video generation and highlighting the possibilities for multi-event conditioning in future models.

Cite

@article{arxiv.2510.03049,
  title  = {When and Where do Events Switch in Multi-Event Video Generation?},
  author = {Ruotong Liao and Guowen Huang and Qing Cheng and Thomas Seidl and Daniel Cremers and Volker Tresp},
  journal= {arXiv preprint arXiv:2510.03049},
  year   = {2025}
}

Comments

Work in Progress. Accepted to ICCV2025 @ LongVid-Foundations

R2 v1 2026-07-01T06:15:22.918Z