‡Equal contribution. * Intern at Google Brain while working on this project.

1

Published as a conference paper at ICLR 2023

Figure 1. Time variable text (i.e. story) conditional video generation. The entire ﬁgure is one con-
tinuous video generated auto-regressively. We start by generating the video conditioned on the ﬁrst
prompt and then after a couple of frames we change the prompt to the next one. Each row contains a
selected number of frames (from left to right in order) while the model was conditioned on that par-
ticular prompt. The model manages to preserve the temporal coherence of the video while adopting
to the new prompt, usually taking the shortest path for the adaption (notice the morphing of the teddy
bear to the panda). Note that the generated video has complex visual features such as reﬂections,
occlusions, interactions and scene transitions. Full video is available at phenaki.github.io.
PHENAKI- VARIABLE LENGTH VIDEO GENERATION FROM OPEN DOMAIN TEXTUAL DESCRIPTIONS