GPS as a Control Signal for Image Generation
We show that the GPS tags contained in photo metadata provide a useful
control signal for image generation. We train GPS-to-image models and use them
for tasks that require a fine-grained understanding of how images vary within a
city. In particular, we train a diffusion model to generate images conditioned
on both GPS and text. The learned model generates images that capture the
distinctive appearance of different neighborhoods, parks, and landmarks. We
also extract 3D models from 2D GPS-to-image models through score distillation
sampling, using GPS conditioning to constrain the appearance of the
reconstruction from each viewpoint. Our evaluations suggest that our
GPS-conditioned models successfully learn to generate images that vary based on
location, and that GPS conditioning improves estimated 3D structure.
67906d622ae55818ddfd0d93
Chao Feng
claimed_verified
2025-01-22T10:08:21.429Z
645ab0b7c266796265baefa4
/avatars/bdac661996b63c4b2a56881707afa01f.svg
Chao Feng
user
chfeng
67906d622ae55818ddfd0d94
Ziyang Chen
67906d622ae55818ddfd0d95
Aleksander Holynski
admin_assigned
2025-01-22T20:49:16.653Z
62f6e2792e53c2efd33faa92
/avatars/85d94b4022577747b8d2d10a82c2f3c7.svg
Aleksander Holynski
user
holynski
67906d622ae55818ddfd0d96
Alexei A. Efros
67906d622ae55818ddfd0d97
Andrew Owens
GPS as a Control Signal for Image Generation
We show that the GPS tags contained in photo metadata provide a useful
control signal for image generation. We train GPS-to-image models and use them
for tasks that require a fine-grained understanding of how images vary within a
city. In particular, we train a diffusion model to generate images conditioned
on both GPS and text. The learned model generates images that capture the
distinctive appearance of different neighborhoods, parks, and landmarks. We
also extract 3D models from 2D GPS-to-image models through score distillation
sampling, using GPS conditioning to constrain the appearance of the
reconstruction from each viewpoint. Our evaluations suggest that our
GPS-conditioned models successfully learn to generate images that vary based on
location, and that GPS conditioning improves estimated 3D structure.
GPS conditioning enhances image generation and 3D reconstruction by capturing location-specific details.
GPS tags image generation diffusion model text conditioning score distillation sampling 3D models 2D GPS-to-image models