There are 33 repositories under kitti-dataset topic.
Python tools for working with KITTI data.
KITTI Object Visualization (Birdview, Volumetric LiDar point cloud )
ICRA 2019 "Self-supervised Sparse-to-Dense: Self-supervised Depth Completion from LiDAR and Monocular Camera"
A 3D computer vision development toolkit based on PaddlePaddle. It supports point-cloud object detection, segmentation, and monocular 3D object detection models.
Optical Flow Prediction with TensorFlow. Implements "PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume," by Deqing Sun et al. (CVPR 2018)
[3DV 2021] DSP-SLAM: Object Oriented SLAM with Deep Shape Priors
3D Object Detection for Autonomous Driving: A Comprehensive Survey (IJCV 2023)
Tutorial for using Kitti dataset easily
Single Image Depth Estimation with Feature Pyramid Network
Convert between visual object detection datasets
Visualising LIDAR data from KITTI dataset.
KITTI data processing and 3D CNN for Vehicle Detection
ROS package for the Perception (Sensor Processing, Detection, Tracking and Evaluation) of the KITTI Vision Benchmark Suite
Efficient monocular visual odometry for ground vehicles on ARM processors
Build a CNN network to predict 3D bounding box of car from 2D image.
Official implementation of the paper: Behind the Scenes: Density Fields for Single View Reconstruction (CVPR 2023)
This repository is an open-source PointPainting package which is easy to understand, deploy and run!
[CVPR 2021] Monocular depth estimation using wavelets for efficiency
Monocular multi-object tracking using simple and complementary 3D and 2D cues (ICRA 2018)
[ECCV-20] Official PyTorch implementation of HoughNet, a voting-based object detector.
Create Dense Depth Map Image for Known Poisitioned Camera from Lidar Point Cloud
A toolkit for Waymo Open Dataset <-> KITTI conversions
Easy description to run and evaluate Lego-LOAM with KITTI-data
3d bounding box estimation from monocular image based on 2d bounding box
Experiments with UNET/FPN models and cityscapes/kitti datasets [Pytorch]
PyTorch Implementation of Unsupervised Depth Completion with Calibrated Backprojection Layers (ORAL, ICCV 2021)
Lidar Odometry and Mapping (J.Zhang et.al). EECS/NAVARCH 568 (Mobile Robotics) Final Project
Steps to reproduce training results for the paper Driving in the Matrix: Can Virtual Worlds Replace Human-Generated Annotations for Real World Tasks?