kitti

Python package for the evaluation of odometry and SLAM

SECOND for KITTI/NuScenes object detection

(IROS 2020, ECCVW 2020) Official Python Implementation for "3D Multi-Object Tracking: A Baseline and New Evaluation Metrics"

A general 3D object detection codebse.

Pytorch version of SfmLearner from Tinghui Zhou et al.

Unsupervised Scale-consistent Depth Learning from Video (IJCV2021 & NeurIPS 2019)

Convert KITTI dataset to ROS bag file the easy way!

Superpoint Implemented in PyTorch: https://arxiv.org/abs/1712.07629

[NeurIPS 2019, Spotlight] Point-Voxel CNN for Efficient 3D Deep Learning

[CVPR 2021] Self-supervised depth estimation from short sequences

Predict dense depth maps from sparse and noisy LiDAR frames guided by RGB images. (Ranked 1st place on KITTI) [2019]

[CVPR 2020, Oral] MaskFlownet: Asymmetric Feature Matching with Learnable Occlusion Mask

Tutorial for using Kitti dataset easily

Visualising LIDAR data from KITTI dataset.

AAAI2023，implementation of "READ: Large-Scale Neural Scene Rendering for Autonomous Driving", the experimental results are significantly better than Nerf-based methods

Python-based optical flow toolkit for existing popular dataset

Current state of supervised and unsupervised depth completion methods

3D detection and tracking viewer (visualization) for kitti & waymo dataset

ROS package for the Perception (Sensor Processing, Detection, Tracking and Evaluation) of the KITTI Vision Benchmark Suite

This is the offical codes for the methods described in the "Feature-metric Loss for Self-supervised Learning of Depth and Egomotion".