Enabling Versatile Controls for Video Diffusion Models

Zhang, Xu, Zhou, Hao, Qin, Haoming, Lu, Xiaobin, Yan, Jiaxing, Wang, Guanzhong, Chen, Zeyu, Liu, Yi

arXiv.org Artificial Intelligence 

Additionally, we design a unified control signal encoding pipeline and a sparse Despite substantial progress in text-to-video generation, residual connection mechanism to efficiently incorporate achieving precise and flexible control over fine-grained control representations. Comprehensive experiments and spatiotemporal attributes remains a significant unresolved human evaluations demonstrate that VCtrl effectively enhances challenge in video generation research. To address these controllability and generation quality. The source limitations, we introduce VCtrl (also termed PP-VCtrl), a code and pre-trained models are publicly available and implemented novel framework designed to enable fine-grained control using the PaddlePaddle framework at https:// over pre-trained video diffusion models in a unified manner.