Semantica: An Adaptable Image-Conditioned Diffusion Model
We investigate the task of adapting image generative models to different
datasets without finetuneing. To this end, we introduce Semantica, an
image-conditioned diffusion model capable of generating images based on the
semantics of a conditioning image. Semantica is trained exclusively on
web-scale image pairs, that is it receives a random image from a webpage as
conditional input and models another random image from the same webpage. Our
experiments highlight the expressivity of pretrained image encoders and
necessity of semantic-based data filtering in achieving high-quality image
generation. Once trained, it can adaptively generate new images from a dataset
by simply using images from that dataset as input. We study the transfer
properties of Semantica on ImageNet, LSUN Churches, LSUN Bedroom and SUN397.
665015de8286a86212b7d3a7
Manoj Kumar
extracted_confirmed
2024-05-27T07:12:15.613Z
6654321cfdf911031c53347a
/avatars/a23d4b5b6d456618f18a87aba4ecd822.svg
Manoj Kumar
user
mechcoder
665015de8286a86212b7d3a8
Neil Houlsby
admin_assigned
2024-05-24T12:03:31.317Z
64a2c7f263f69fb98d3bfdb4
/avatars/a362a236c0654b7605dcb7673e309335.svg
Neil Houlsby
user
neilhoulsby
665015de8286a86212b7d3a9
Emiel Hoogeboom
extracted_confirmed
2024-10-28T19:59:56.457Z
671feaa3e269c38584cb065f
/avatars/d7bc35ab98b208ef1d009aa9b629682a.svg
Emiel Hoogeboom
user
Emiel2
Semantica: An Adaptable Image-Conditioned Diffusion Model
We investigate the task of adapting image generative models to different
datasets without finetuneing. To this end, we introduce Semantica, an
image-conditioned diffusion model capable of generating images based on the
semantics of a conditioning image. Semantica is trained exclusively on
web-scale image pairs, that is it receives a random image from a webpage as
conditional input and models another random image from the same webpage. Our
experiments highlight the expressivity of pretrained image encoders and
necessity of semantic-based data filtering in achieving high-quality image
generation. Once trained, it can adaptively generate new images from a dataset
by simply using images from that dataset as input. We study the transfer
properties of Semantica on ImageNet, LSUN Churches, LSUN Bedroom and SUN397.
Semantica, an image-conditioned diffusion model, generates high-quality images based on semantic information and adapts to different datasets without fine-tuning.
image-conditioned diffusion model web-scale image pairs pretrained image encoders semantic-based data filtering transfer properties