pseudo-lidar

This repository provides awesome research papers for autonomous driving perception. If you do find a problem or have any suggestions, please raise this as an issue or make a pull request with information (format of the repo): Research paper title, datasets, metrics, objects, source code, publisher, and year.

Official Pytorch implementation of the "Sparse LiDAR and Stereo Fusion (SLS-Fusion) for Depth Estimation and 3D Object Detection" paper.

ROS package for stereo matching and point cloud projection using AANet (Adaptive Aggregation Network for Efficient Stereo Matching, CVPR 2020)

Initialisation-free camera–LiDAR self-calibration via pseudo-LiDAR BEV pillars (BMVC 2023). Recovers extreme decalibration — up to ±180° yaw — in one shot, then refines through a 3-stage coarse-to-fine cascade.

Autonomous Driving – object classification based on 3D point cloud data, for the course of TAA