Computer Science > Computer Vision and Pattern Recognition
arXiv:2301.05225 (cs)
[Submitted on 12 Jan 2023 (v1), last revised 17 Apr 2023 (this version, v2)]
Title:Domain Expansion of Image Generators
Authors:Yotam Nitzan,Michaël Gharbi,Richard Zhang,Taesung Park,Jun-Yan Zhu,Daniel Cohen-Or,Eli Shechtman
View a PDF of the paper titled Domain Expansion of Image Generators, by Yotam Nitzan and 6 other authors
View PDFAbstract:Can one inject new concepts into an already trained generative model, while respecting its existing structure and knowledge? We propose a new task - domain expansion - to address this. Given a pretrained generator and novel (but related) domains, we expand the generator to jointly model all domains, old and new, harmoniously. First, we note the generator contains a meaningful, pretrained latent space. Is it possible to minimally perturb this hard-earned representation, while maximally representing the new domains? Interestingly, we find that the latent space offers unused, "dormant" directions, which do not affect the output. This provides an opportunity: By "repurposing" these directions, we can represent new domains without perturbing the original representation. In fact, we find that pretrained generators have the capacity to add several - even hundreds - of new domains! Using our expansion method, one "expanded" model can supersede numerous domain-specific models, without expanding the model size. Additionally, a single expanded generator natively supports smooth transitions between domains, as well as composition of domains. Code and project page available atthis https URL.
| Comments: | Project Page and code are available atthis https URL. CVPR 2023 Camera-Ready |
| Subjects: | Computer Vision and Pattern Recognition (cs.CV); Graphics (cs.GR); Machine Learning (cs.LG) |
| Cite as: | arXiv:2301.05225 [cs.CV] |
| (orarXiv:2301.05225v2 [cs.CV] for this version) | |
| https://doi.org/10.48550/arXiv.2301.05225 arXiv-issued DOI via DataCite |
Submission history
From: Yotam Nitzan [view email][v1] Thu, 12 Jan 2023 18:59:47 UTC (23,133 KB)
[v2] Mon, 17 Apr 2023 11:24:07 UTC (23,368 KB)
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View a PDF of the paper titled Domain Expansion of Image Generators, by Yotam Nitzan and 6 other authors
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