Art-Free Generative Models: Art Creation Without Graphic Art Knowledge
We explore the question: "How much prior art knowledge is needed to create
art?" To investigate this, we propose a text-to-image generation model trained
without access to art-related content. We then introduce a simple yet effective
method to learn an art adapter using only a few examples of selected artistic
styles. Our experiments show that art generated using our method is perceived
by users as comparable to art produced by models trained on large, art-rich
datasets. Finally, through data attribution techniques, we illustrate how
examples from both artistic and non-artistic datasets contributed to the
creation of new artistic styles.
674ea7dcb311aeec3f329ae5
Hui Ren
claimed_verified
2024-12-03T09:56:40.473Z
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Hui Ren
user
rhfeiyang
674ea7dcb311aeec3f329ae6
Joanna Materzynska
admin_assigned
2024-12-03T15:25:28.758Z
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Joanna Materzynska
user
jomat
674ea7dcb311aeec3f329ae7
Rohit Gandikota
admin_assigned
2024-12-03T16:04:26.266Z
636daf1b56c0762cfda074b5
/avatars/f44be5eb110acfa2efbd09de6b416239.svg
Rohit Gandikota
user
RohitGandikota
674ea7dcb311aeec3f329ae8
David Bau
admin_assigned
2024-12-03T16:04:19.664Z
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David Bau
user
davidbau
674ea7dcb311aeec3f329ae9
Antonio Torralba
admin_assigned
2024-12-03T16:04:13.407Z
6744c6ec6ec99a37d4ba9235
/avatars/a5384b63bb615192f6fa157c6ea89e92.svg
Antonio
user
Antoniotorralbaborruel
Art-Free Generative Models: Art Creation Without Graphic Art Knowledge
We explore the question: "How much prior art knowledge is needed to create
art?" To investigate this, we propose a text-to-image generation model trained
without access to art-related content. We then introduce a simple yet effective
method to learn an art adapter using only a few examples of selected artistic
styles. Our experiments show that art generated using our method is perceived
by users as comparable to art produced by models trained on large, art-rich
datasets. Finally, through data attribution techniques, we illustrate how
examples from both artistic and non-artistic datasets contributed to the
creation of new artistic styles.
A text-to-image generation model trained without art-related content can produce artwork of comparable quality to models using large art-rich datasets by using a learned art adapter.
text-to-image generation art adapter art-related content artistic styles data attribution techniques