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250508s2025 xx |||||o 00| ||eng c |
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|a 10.1109/TVCG.2025.3558468
|2 doi
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2 |
|a pubmed25n1561.xml
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|a DE-627
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|e rakwb
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| 041 |
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|a eng
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| 100 |
1 |
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|a Wang, Yifan
|e verfasserin
|4 aut
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| 245 |
1 |
0 |
|a Stylizing Sparse-View 3D Scenes With Hierarchical Neural Representation
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| 264 |
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1 |
|c 2025
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| 336 |
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|a Text
|b txt
|2 rdacontent
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| 337 |
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|a ƒaComputermedien
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|2 rdamedia
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| 338 |
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|a ƒa Online-Ressource
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|2 rdacarrier
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| 500 |
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|a Date Revised 08.09.2025
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|a published: Print
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|a Citation Status PubMed-not-MEDLINE
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| 520 |
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|a 3D scene stylization refers to generating stylized images of the scene at arbitrary novel view angles following a given set of style images while ensuring consistency when rendered from different views. Recently, several 3D style transfer methods leveraging the scene reconstruction capabilities of pre-trained neural radiance fields (NeRF) have been proposed. To successfully stylize a scene this way, one must first reconstruct a photo-realistic radiance field from collected images of the scene. However, when only sparse input views are available, pre-trained few-shot NeRFs often suffer from high-frequency artifacts, which are generated as a by-product of high-frequency details for improving reconstruction quality. Is it possible to generate more faithful stylized scenes from sparse inputs by directly optimizing encoding-based scene representation with target style? In this paper, we consider the stylization of sparse-view scenes in terms of disentangling content semantics and style textures. We propose a coarse-to-fine sparse-view scene stylization framework, where a novel hierarchical encoding-based neural representation is designed to generate high-quality stylized scenes directly from implicit scene representations. We also propose a new optimization strategy with content strength annealing to achieve realistic stylization and better content preservation. Extensive experiments demonstrate that our method can achieve high-quality stylization of sparse-view scenes and outperforms fine-tuning-based baselines in terms of stylization quality and efficiency
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| 650 |
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4 |
|a Journal Article
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| 700 |
1 |
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|a Gao, Ang
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Gong, Yi
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Zeng, Yuan
|e verfasserin
|4 aut
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| 773 |
0 |
8 |
|i Enthalten in
|t IEEE transactions on visualization and computer graphics
|d 1996
|g 31(2025), 10 vom: 26. Sept., Seite 7876-7889
|w (DE-627)NLM098269445
|x 1941-0506
|7 nnas
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| 773 |
1 |
8 |
|g volume:31
|g year:2025
|g number:10
|g day:26
|g month:09
|g pages:7876-7889
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| 856 |
4 |
0 |
|u http://dx.doi.org/10.1109/TVCG.2025.3558468
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|d 31
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