Python package for the evaluation of odometry and SLAM

SECOND for KITTI/NuScenes object detection

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

A general 3D object detection codebse.

Pytorch version of SfmLearner from Tinghui Zhou et al.

Convert KITTI dataset to ROS bag file the easy way!

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

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

[ICCV 2019] Official implementation of "MonoLoco: Monocular 3D Pedestrian Localization and Uncertainty Estimation" in PyTorch + Social Distancing

Tutorial for using Kitti dataset easily

Python-based optical flow toolkit for existing popular dataset

Visualising LIDAR data from KITTI dataset.

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

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

Monocular multi-object tracking using simple and complementary 3D and 2D cues (ICRA 2018)

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

Papers and code related to 3D object detection

Detect object in 3D with Point Cloud and Image.

Efficient monocular visual odometry for ground vehicles on ARM processors

Unsupervised Depth Completion from Visual Inertial Odometry (in RA-L January 2020 & ICRA 2020)

PyTorch implementation for 3D Bounding Box Estimation Using Deep Learning and Geometry

A cross-platform image annotation tool for machine learning

A customized implementation of the paper "StereoNet: guided hierarchical refinement for real-time edge-aware depth prediction"

Estimating distance to objects in the scene using detection information

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

Weakly Supervised 3D Object Detection from Point Clouds (VS3D), ACM MM 2020

Easy description to run and evaluate Lego-LOAM with KITTI-data

Current state of supervised and unsupervised depth completion methods

A New 3D Detector. Code Will be made public.

Complete the conversion from the .bag file to the .png and .bin files. Includes .bag file decoding, pcd2bin and file directory extraction.