VidPanos: Generative Panoramic Videos from Casual Panning Videos
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.
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Jingwei Ma
admin_assigned
2024-10-18T12:54:07.209Z
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Jingwei Ma
user
jingweim
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Erika Lu
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Roni Paiss
admin_assigned
2024-10-18T12:54:20.845Z
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Roni Paiss
user
RoniPaiss
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Shiran Zada
admin_assigned
2024-10-18T12:54:26.118Z
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Shiran Zada
user
shiranzada
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Aleksander Holynski
admin_assigned
2024-10-18T12:54:32.095Z
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Aleksander Holynski
user
holynski
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Tali Dekel
admin_assigned
2024-10-18T12:54:38.194Z
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Tali Dekel
user
talidekel
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Brian Curless
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Michael Rubinstein
6711da38e6f26ad913eac181
Forrester Cole
extracted_pending
2024-10-18T03:47:06.381Z
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Forrester Cole
user
fcole
VidPanos: Generative Panoramic Videos from Casual Panning Videos
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.
A method for synthesizing panoramic videos from panning recordings is presented, using video generation models to handle space-time outpainting for moving objects and realistic motion.
panoramic image stitching panning video panorama synthesis space-time outpainting generative video models video content motion in-the-wild scenes