SynReconEval: Synthetic dataset creator for photogrammetric reconstruction evaluation
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