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NERFBK: A High-Quality Benchmark for NERF-Based 3D Reconstruction

arXiv 2306.06300 ↗First posted 9 Jun 2023cs.CV cs.AI cs.GRcited by 0

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Abstract (arXiv)

This paper introduces a new real and synthetic dataset called NeRFBK specifically designed for testing and comparing NeRF-based 3D reconstruction algorithms. High-quality 3D reconstruction has significant potential in various fields, and advancements in image-based algorithms make it essential to evaluate new advanced techniques. However, gathering diverse data with precise ground truth is challenging and may not encompass all relevant applications. The NeRFBK dataset addresses this issue by providing multi-scale, indoor and outdoor datasets with high-resolution images and videos and camera parameters for testing and comparing NeRF-based algorithms. This paper presents the design and creation of the NeRFBK benchmark, various examples and application scenarios, and highlights its potential for advancing the field of 3D reconstruction.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 35 of its 79 references that are in the map. First posted on arXiv 9 Jun 2023.

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35 of 79 references.

References · 35

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23 more
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