SynReconEval: Synthetic dataset creator for photogrammetric reconstruction evaluation

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Authors: Pablo Garrido, Eduard Pujol, Antoni Chica
Cited by: 0
References: 6

Abstract

SynReconEval is an open-source framework for generating synthetic datasets to benchmark photogrammetric and neural 3D reconstruction methods. It leverages Blender to render controlled RGB images, depth maps, and normal maps with full camera parameters, which are then processed by reconstruction pipelines. The reconstructed models are evaluated against ground-truth geometry using a wide range of metrics, including precision, recall, and spatial error distributions. The system’s modular design allows for easy integration of new renderers, algorithms, and evaluation criteria, enabling large-scale, reproducible, and customizable assessment of reconstruction performance.

Fields of Study & Subjects

3D Surveying and Cultural Heritage Remote Sensing and LiDAR Applications Robotics and Sensor-Based Localization

Publication details

Journal / source
SoftwareX
Volume
34
Pages
102744–102744
Publication date
26 May 2026
Language
EN