GO-NeRF: Generating Objects in Neural Radiance Fields for Virtual Reality Content Creation Article Swipe
Peng Dai
,
Feitong Tan
,
Xin Yu
,
Yinda Zhang
,
Xiaojuan Qi
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2401.05750
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2401.05750
Virtual environments (VEs) are pivotal for virtual, augmented, and mixed reality systems. Despite advances in 3D generation and reconstruction, the direct creation of 3D objects within an established 3D scene (represented as NeRF) for novel VE creation remains a relatively unexplored domain. This process is complex, requiring not only the generation of high-quality 3D objects but also their seamless integration into the existing scene. To this end, we propose a novel pipeline featuring an intuitive interface, dubbed GO-NeRF. Our approach takes text prompts and user-specified regions as inputs and leverages the scene context to generate 3D objects within the scene. We employ a compositional rendering formulation that effectively integrates the generated 3D objects into the scene, utilizing optimized 3D-aware opacity maps to avoid unintended modifications to the original scene. Furthermore, we develop tailored optimization objectives and training strategies to enhance the model's ability to capture scene context and mitigate artifacts, such as floaters, that may occur while optimizing 3D objects within the scene. Extensive experiments conducted on both forward-facing and 360o scenes demonstrate the superior performance of our proposed method in generating objects that harmonize with surrounding scenes and synthesizing high-quality novel view images. We are committed to making our code publicly available.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2401.05750
- https://arxiv.org/pdf/2401.05750
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4390833317
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4390833317Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2401.05750Digital Object Identifier
- Title
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GO-NeRF: Generating Objects in Neural Radiance Fields for Virtual Reality Content CreationWork title
- Type
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preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2024Year of publication
- Publication date
-
2024-01-11Full publication date if available
- Authors
-
Peng Dai, Feitong Tan, Xin Yu, Yinda Zhang, Xiaojuan QiList of authors in order
- Landing page
-
https://arxiv.org/abs/2401.05750Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2401.05750Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2401.05750Direct OA link when available
- Concepts
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Computer science, Exploit, Artificial intelligence, Computer vision, Rendering (computer graphics), Context (archaeology), Object (grammar), Process (computing), Radiance, Computer graphics (images), Biology, Optics, Operating system, Computer security, Paleontology, PhysicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1Per-year citation counts (last 5 years)
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.optimized | 117 |
| abstract_inverted_index.rendering | 104 |
| abstract_inverted_index.requiring | 46 |
| abstract_inverted_index.utilizing | 116 |
| abstract_inverted_index.artifacts, | 149 |
| abstract_inverted_index.augmented, | 7 |
| abstract_inverted_index.available. | 202 |
| abstract_inverted_index.generating | 181 |
| abstract_inverted_index.generation | 16, 50 |
| abstract_inverted_index.integrates | 108 |
| abstract_inverted_index.interface, | 75 |
| abstract_inverted_index.objectives | 134 |
| abstract_inverted_index.optimizing | 157 |
| abstract_inverted_index.relatively | 39 |
| abstract_inverted_index.strategies | 137 |
| abstract_inverted_index.unexplored | 40 |
| abstract_inverted_index.unintended | 123 |
| abstract_inverted_index.demonstrate | 172 |
| abstract_inverted_index.effectively | 107 |
| abstract_inverted_index.established | 27 |
| abstract_inverted_index.experiments | 164 |
| abstract_inverted_index.formulation | 105 |
| abstract_inverted_index.integration | 59 |
| abstract_inverted_index.performance | 175 |
| abstract_inverted_index.surrounding | 186 |
| abstract_inverted_index.(represented | 30 |
| abstract_inverted_index.Furthermore, | 129 |
| abstract_inverted_index.environments | 1 |
| abstract_inverted_index.high-quality | 52, 190 |
| abstract_inverted_index.optimization | 133 |
| abstract_inverted_index.synthesizing | 189 |
| abstract_inverted_index.compositional | 103 |
| abstract_inverted_index.modifications | 124 |
| abstract_inverted_index.forward-facing | 168 |
| abstract_inverted_index.user-specified | 84 |
| abstract_inverted_index.reconstruction, | 18 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 5 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/14 |
| sustainable_development_goals[0].score | 0.44999998807907104 |
| sustainable_development_goals[0].display_name | Life below water |
| citation_normalized_percentile |