VidPanos: Generative Panoramic Videos from Casual Panning Videos
Authors: name: Jingwei Ma, name: Erika Lu, name: Roni Paiss, name: Shiran Zada, name: Aleksander Holynski, name: Tali Dekel, name: Brian Curless, name: Michael Rubinstein, name: Forrester Cole

Panoramic image stitching provides a unified, wide-angle view of a scene that
extends beyond the camera's field of view. Stitching frames of a panning video
into a panoramic photograph is a well-understood problem for stationary scenes,
but when objects are moving, a still panorama cannot capture the scene. We
present a method for synthesizing a panoramic video from a casually-captured
panning video, as if the original video were captured with a wide-angle camera.
We pose panorama synthesis as a space-time outpainting problem, where we aim to
create a full panoramic video of the same length as the input video. Consistent
completion of the space-time volume requires a powerful, realistic prior over
video content and motion, for which we adapt generative video models. Existing
generative models do not, however, immediately extend to panorama completion,
as we show. We instead apply video generation as a component of our panorama
synthesis system, and demonstrate how to exploit the strengths of the models
while minimizing their limitations. Our system can create video panoramas for a
range of in-the-wild scenes including people, vehicles, and flowing water, as
well as stationary background features.