Text2Video-Zero Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generators is by Levon Khachatryan, Andranik Movsisyan, Vahram Tadevosyan, Roberto Henschel, Zhangyang Wang, Shant Navasardyan, Humphrey Shi. Text2Video-Zero enables zero-shot video generation using either: A textual prompt A prompt combined with guidance from poses or edges Video Instruct-Pix2Pix (instruction-guided video editing) Results are temporally consistent and closely follow the guidance and textual prompts.  The abstract from the paper is: Recent text-to-video generation approaches rely on computationally heavy training and require large-scale video datasets. In this paper, we introduce a new task of zero-shot text-to-video generation and propose a low-cost approach (without any training or optimization) by leveraging the power of existing text-to-image synthesis methods (e.g., Stable Diffusion), making them suitable for the video domain.