Neural Free-Viewpoint Performance Rendering under Complex Human-object Interactions Article Swipe
YOU?
·
· 2021
· Open Access
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· DOI: https://doi.org/10.48550/arxiv.2108.00362
4D reconstruction of human-object interaction is critical for immersive VR/AR experience and human activity understanding. Recent advances still fail to recover fine geometry and texture results from sparse RGB inputs, especially under challenging human-object interactions scenarios. In this paper, we propose a neural human performance capture and rendering system to generate both high-quality geometry and photo-realistic texture of both human and objects under challenging interaction scenarios in arbitrary novel views, from only sparse RGB streams. To deal with complex occlusions raised by human-object interactions, we adopt a layer-wise scene decoupling strategy and perform volumetric reconstruction and neural rendering of the human and object. Specifically, for geometry reconstruction, we propose an interaction-aware human-object capture scheme that jointly considers the human reconstruction and object reconstruction with their correlations. Occlusion-aware human reconstruction and robust human-aware object tracking are proposed for consistent 4D human-object dynamic reconstruction. For neural texture rendering, we propose a layer-wise human-object rendering scheme, which combines direction-aware neural blending weight learning and spatial-temporal texture completion to provide high-resolution and photo-realistic texture results in the occluded scenarios. Extensive experiments demonstrate the effectiveness of our approach to achieve high-quality geometry and texture reconstruction in free viewpoints for challenging human-object interactions.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2108.00362
- https://arxiv.org/pdf/2108.00362
- OA Status
- green
- Cited By
- 1
- References
- 18
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3207655919
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3207655919Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2108.00362Digital Object Identifier
- Title
-
Neural Free-Viewpoint Performance Rendering under Complex Human-object InteractionsWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-08-01Full publication date if available
- Authors
-
Guoxing Sun, Xin Chen, Yizhang Chen, Anqi Pang, Pei Lin, Yuheng Jiang, Lan Xu, Jingyi Yu, Jingya WangList of authors in order
- Landing page
-
https://arxiv.org/abs/2108.00362Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2108.00362Direct 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/2108.00362Direct OA link when available
- Concepts
-
Rendering (computer graphics), Artificial intelligence, Computer science, Computer vision, RGB color model, Object (grammar), Iterative reconstruction, Computer graphics (images)Top concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
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2021: 1Per-year citation counts (last 5 years)
- References (count)
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18Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.direction-aware | 155 |
| abstract_inverted_index.high-resolution | 166 |
| abstract_inverted_index.photo-realistic | 55, 168 |
| abstract_inverted_index.reconstruction, | 106 |
| abstract_inverted_index.reconstruction. | 141 |
| abstract_inverted_index.spatial-temporal | 161 |
| abstract_inverted_index.interaction-aware | 110 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 9 |
| citation_normalized_percentile |