PointPillars for Argoverse object detection

working repository

Experimental dockerized workspace for 2D/3D object detection, segmentation, tracking, anything related to perception

Convert pointpillars Pytorch Model To ONNX for TensorRT Inference

Anchor-Free LiDAR object detetor for 3d Object detection

PAPC is a deep learning for point clouds platform based on pure PaddlePaddle

Implementation of PointPillars paper in Unity for VRChat

Implementation of PointPillars in PyTorch for KITTI 3D Object Detetcion

Implementation of PointPillars Network with LiDAR-camera fusion for 3D Object Detection in Autonomous Driving.

Frustum-PointPillars: A Multi-Stage Approach for 3D Object Detection using RGB Camera and LiDAR

This repository contains supplementary materials for a Master Thesis project on efficient object detection. It includes a series of video demonstrations showcasing the performance of networks trained and tested on synthetic (AVX) and real-world (KITTI) data sets.

A Simple PointPillars PyTorch Implementation for 3D Lidar(KITTI) Detection.

This repository contains a Master's Thesis on enhancing LiDAR-based 3D Object Detection in autonomous vehicles using synthetic data. The research explores the use of the Ansys AVxcelerate Sensors Simulator (AVX) to create synthetic point clouds. It includes a hybrid training approach, experimental design, results, and related scripts.

Deployment of 3D-Detection and Tracking pipeline in simulation based on rosbags and real-time.

A Simple PointPillars PyTorch Implementation for 3D LiDAR(KITTI) Detection.

A 3D computer vision development toolkit based on PaddlePaddle. It supports point-cloud object detection, segmentation, and monocular 3D object detection models.