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|a 10.1109/TPAMI.2024.3411051
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|a eng
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| 100 |
1 |
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|a Lu, Yuqin
|e verfasserin
|4 aut
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| 245 |
1 |
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|a 3D Snapshot
|b Invertible Embedding of 3D Neural Representations in a Single Image
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|a Date Revised 25.06.2024
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|a Citation Status Publisher
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|a 3D neural rendering enables photo-realistic reconstruction of a specific scene by encoding discontinuous inputs into a neural representation. Despite the remarkable rendering results, the storage of network parameters is not transmission-friendly and not extendable to metaverse applications. In this paper, we propose an invertible neural rendering approach that enables generating an interactive 3D model from a single image (i.e., 3D Snapshot). Our idea is to distill a pre-trained neural rendering model (e.g., NeRF) into a visualizable image form that can then be easily inverted back to a neural network. To this end, we first present a neural image distillation method to optimize three neural planes for representing the original neural rendering model. However, this representation is noisy and visually meaningless. We thus propose a dynamic invertible neural network to embed this noisy representation into a plausible image representation of the scene. We demonstrate promising reconstruction quality quantitatively and qualitatively, by comparing to the original neural rendering model, as well as video-based invertible methods. On the other hand, our method can store dozens of NeRFs with a compact restoration network (5MB), and embedding each 3D scene takes up only 160KB of storage. More importantly, our approach is the first solution that allows embedding a neural rendering model into image representations, which enables applications like creating an interactive 3D model from a printed image in the metaverse
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|a Journal Article
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1 |
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|a Deng, Bailin
|e verfasserin
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| 700 |
1 |
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|a Zhong, Zhixuan
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Zhang, Tianle
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Quan, Yuhui
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Cai, Hongmin
|e verfasserin
|4 aut
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| 700 |
1 |
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|a He, Shengfeng
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE transactions on pattern analysis and machine intelligence
|d 1979
|g PP(2024) vom: 07. Juni
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|x 1939-3539
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|g year:2024
|g day:07
|g month:06
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|u http://dx.doi.org/10.1109/TPAMI.2024.3411051
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