maudzung/Complex-YOLOv4-Pytorch
PyTorch implementation of Complex-YOLO for real-time 3D object detection on LiDAR point clouds.
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This repository provides a PyTorch implementation of Complex-YOLO, a deep learning architecture derived from YOLOv4 designed for 3D object detection using LiDAR point clouds. It supports distributed data parallel training, uses GIoU loss for rotated bounding box optimization, and includes mosaic/cutout data augmentation. The model is intended for autonomous driving applications where it detects objects like vehicles and pedestrians from 3D sensor data.
Frequently asked
- What is maudzung/Complex-YOLOv4-Pytorch?
- PyTorch implementation of Complex-YOLO for real-time 3D object detection on LiDAR point clouds.
- Is Complex-YOLOv4-Pytorch open source?
- Yes — maudzung/Complex-YOLOv4-Pytorch is open source, released under the GPL-3.0 license.
- What language is Complex-YOLOv4-Pytorch written in?
- maudzung/Complex-YOLOv4-Pytorch is primarily written in Python.
- How popular is Complex-YOLOv4-Pytorch?
- maudzung/Complex-YOLOv4-Pytorch has 1.3k stars on GitHub.
- Where can I find Complex-YOLOv4-Pytorch?
- maudzung/Complex-YOLOv4-Pytorch is on GitHub at https://github.com/maudzung/Complex-YOLOv4-Pytorch.