GTA-3D Dataset
A synthetic dataset of 2D imagery, 3D point clouds, and 3D vehicle bounding box labels generated using the Grand Theft Auto 5 game engine.
What is GTA-3D Dataset?
GTA-3D Dataset is a synthetic dataset designed for 3D object localization research. It provides 2D imagery, 3D point clouds, and 3D vehicle bounding box labels generated using the Grand Theft Auto 5 game engine. The dataset solves the problem of scarce, accurately labeled 3D data for training computer vision models.
Researchers and developers working on 3D object detection, localization, and autonomous vehicle perception systems.
It offers a large-scale, high-resolution synthetic dataset with precise 3D labels, which is more cost-effective and scalable than collecting real-world data. The included Python utilities make it easy to integrate into machine learning pipelines.
Overview
A dataset of 2D imagery, 3D point cloud data, and 3D vehicle bounding box labels all generated using the Grand Theft Auto 5 game engine.
Use Cases
Best For
- Training 3D object detection models for autonomous vehicles
- Research on synthetic data generation for computer vision
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