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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2505.00734 |
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| _version_ | 1866909598656495616 |
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| author | Joshi, Neil Carney, Joshua Kuo, Nathanael Li, Homer Peng, Cheng Brown, Myron |
| author_facet | Joshi, Neil Carney, Joshua Kuo, Nathanael Li, Homer Peng, Cheng Brown, Myron |
| contents | Production of photorealistic, navigable 3D site models requires a large volume of carefully collected images that are often unavailable to first responders for disaster relief or law enforcement. Real-world challenges include limited numbers of images, heterogeneous unposed cameras, inconsistent lighting, and extreme viewpoint differences for images collected from varying altitudes. To promote research aimed at addressing these challenges, we have developed the first public benchmark dataset for 3D reconstruction and novel view synthesis based on multiple calibrated ground-level, security-level, and airborne cameras. We present datasets that pose real-world challenges, independently evaluate calibration of unposed cameras and quality of novel rendered views, demonstrate baseline performance using recent state-of-practice methods, and identify challenges for further research. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_00734 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Unconstrained Large-scale 3D Reconstruction and Rendering across Altitudes Joshi, Neil Carney, Joshua Kuo, Nathanael Li, Homer Peng, Cheng Brown, Myron Computer Vision and Pattern Recognition Image and Video Processing Production of photorealistic, navigable 3D site models requires a large volume of carefully collected images that are often unavailable to first responders for disaster relief or law enforcement. Real-world challenges include limited numbers of images, heterogeneous unposed cameras, inconsistent lighting, and extreme viewpoint differences for images collected from varying altitudes. To promote research aimed at addressing these challenges, we have developed the first public benchmark dataset for 3D reconstruction and novel view synthesis based on multiple calibrated ground-level, security-level, and airborne cameras. We present datasets that pose real-world challenges, independently evaluate calibration of unposed cameras and quality of novel rendered views, demonstrate baseline performance using recent state-of-practice methods, and identify challenges for further research. |
| title | Unconstrained Large-scale 3D Reconstruction and Rendering across Altitudes |
| topic | Computer Vision and Pattern Recognition Image and Video Processing |
| url | https://arxiv.org/abs/2505.00734 |