5 papers
MEV: A Multi-Event Video Dataset for Long-Take Generation
Peiyuan Zhu, Shaoan Xie, Yifan Shen +4
Current datasets for text-to-video generation are largely limited to short clips depicting a single event or coarse-grained captions. As a result, they provide limited supervision…
Prospective Forcing: Learning to Look Ahead for Autoregressive Long Video Diffusion
Yifan Shen, Yewei Xia, Gongxu Luo +6
Autoregressive video generators synthesize long videos through chunk-wise rollouts, yet they are typically trained to predict only the immediate future. This limited prediction hor…
MoVA: Learning Asymmetric Dual Projections for Modular Long Video-Text Alignment
Peiyuan Zhu, Shaoan Xie, Zijian Li +5
Contrastive pre-training has propelled video-text alignment, yet models often inherit the critical limitations of their image-text predecessors like CLIP, resulting in entangled re…
CausalVerse: Benchmarking Causal Representation Learning with Configurable High-Fidelity Simulations
Guangyi Chen, Yunlong Deng, Peiyuan Zhu +4
Causal Representation Learning (CRL) aims to uncover the data-generating process and identify the underlying causal variables and relations, whose evaluation remains inherently cha…
Controllable Video Generation with Provable Disentanglement
Yifan Shen, Peiyuan Zhu, Zijian Li +6
Controllable video generation remains a significant challenge, despite recent advances in generating high-quality and consistent videos. Most existing methods for controlling video…