One2Avatar: Generative Implicit Head Avatar For Few-shot User Adaptation Article Swipe
Zhixuan Yu
,
Ziqian Bai
,
Abhimitra Meka
,
Feitong Tan
,
Qiangeng Xu
,
Rohit Pandey
,
Sean Fanello
,
Hyun Soo Park
,
Yinda Zhang
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2402.11909
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2402.11909
Traditional methods for constructing high-quality, personalized head avatars from monocular videos demand extensive face captures and training time, posing a significant challenge for scalability. This paper introduces a novel approach to create high quality head avatar utilizing only a single or a few images per user. We learn a generative model for 3D animatable photo-realistic head avatar from a multi-view dataset of expressions from 2407 subjects, and leverage it as a prior for creating personalized avatar from few-shot images. Different from previous 3D-aware face generative models, our prior is built with a 3DMM-anchored neural radiance field backbone, which we show to be more effective for avatar creation through auto-decoding based on few-shot inputs. We also handle unstable 3DMM fitting by jointly optimizing the 3DMM fitting and camera calibration that leads to better few-shot adaptation. Our method demonstrates compelling results and outperforms existing state-of-the-art methods for few-shot avatar adaptation, paving the way for more efficient and personalized avatar creation.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2402.11909
- https://arxiv.org/pdf/2402.11909
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4391987800
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4391987800Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2402.11909Digital Object Identifier
- Title
-
One2Avatar: Generative Implicit Head Avatar For Few-shot User AdaptationWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-02-19Full publication date if available
- Authors
-
Zhixuan Yu, Ziqian Bai, Abhimitra Meka, Feitong Tan, Qiangeng Xu, Rohit Pandey, Sean Fanello, Hyun Soo Park, Yinda ZhangList of authors in order
- Landing page
-
https://arxiv.org/abs/2402.11909Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2402.11909Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2402.11909Direct OA link when available
- Concepts
-
Avatar, Head (geology), Adaptation (eye), Generative grammar, Computer science, Shot (pellet), Human–computer interaction, Artificial intelligence, Psychology, Geology, Neuroscience, Chemistry, Organic chemistry, GeomorphologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.backbone, | 96 |
| abstract_inverted_index.challenge | 21 |
| abstract_inverted_index.creation. | 157 |
| abstract_inverted_index.effective | 103 |
| abstract_inverted_index.efficient | 153 |
| abstract_inverted_index.extensive | 12 |
| abstract_inverted_index.monocular | 9 |
| abstract_inverted_index.subjects, | 65 |
| abstract_inverted_index.utilizing | 36 |
| abstract_inverted_index.animatable | 53 |
| abstract_inverted_index.compelling | 137 |
| abstract_inverted_index.generative | 49, 84 |
| abstract_inverted_index.introduces | 26 |
| abstract_inverted_index.multi-view | 59 |
| abstract_inverted_index.optimizing | 121 |
| abstract_inverted_index.Traditional | 0 |
| abstract_inverted_index.adaptation, | 147 |
| abstract_inverted_index.adaptation. | 133 |
| abstract_inverted_index.calibration | 127 |
| abstract_inverted_index.expressions | 62 |
| abstract_inverted_index.outperforms | 140 |
| abstract_inverted_index.significant | 20 |
| abstract_inverted_index.constructing | 3 |
| abstract_inverted_index.demonstrates | 136 |
| abstract_inverted_index.personalized | 5, 74, 155 |
| abstract_inverted_index.scalability. | 23 |
| abstract_inverted_index.3DMM-anchored | 92 |
| abstract_inverted_index.auto-decoding | 108 |
| abstract_inverted_index.high-quality, | 4 |
| abstract_inverted_index.photo-realistic | 54 |
| abstract_inverted_index.state-of-the-art | 142 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 9 |
| citation_normalized_percentile |