A unified, searchable, and maintainable catalog of 3D object-detection methods and benchmarks—born from a Master’s thesis and implemented as a Jekyll/GitHub Pages site.
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📊 Datasets
Overview of major 3D-OD benchmarks (KITTI, nuScenes, Waymo, …) and their core statistics. -
🛠️ Models
Filterable, sortable database of camera-only, LiDAR-only, and multi-modal fusion methods.
• Search by name
• Filter by sensor & representation
• Sort by year, mAP, runtime, code availability -
📚 References
Fully formatted bibliography of every paper, library, and dataset used. -
👤 About
Background on the underlying Master’s thesis, site construction, and contact details.
Contributions are very welcome! Please:
Open an issue to discuss new features or data.
Send a pull request with your changes (new methods, datasets, bug fixes).
Ensure your additions follow the existing data format.
This project is licensed under the GPL3.0 License. Feel free to reuse the data and code—just please cite the original thesis!
If you use this site, data, or code, please cite our publication:
Valverde, M., Moutinho, A., & Zacchi, J. V. (2025). A Survey of Deep Learning-Based 3D Object Detection Methods for Autonomous Driving Across Different Sensor Modalities. Sensors.