Carlafox: Towards reliable open-source 3D perception Overview Key takeaways Data Collection Training 3D Perception Models on CARLA dataset A closer look into SFA3D Optimising with TensorRT Testing Outlook Furthermore, we use the Carlafox tool to generate a dataset consisting of 10,000+ samples and use this dataset to train SFA3D, a fast open-source 3D object detection neural network. We trained quite a few LiDAR-based networks, namely PointRCNN, PVRCNN, and SFA3D, and a Multimodal(RGB + LiDAR) 3D object detection model, i.e. MVXNet on the CARLA synthetic dataset but fine-tuned only one of these i.e., SFA3D, mainly because it is faster and uses less memory without much loss in performance.