Python tools for working with KITTI data.
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Updated
Oct 16, 2023 - Python
Python tools for working with KITTI data.
KITTI Object Visualization (Birdview, Volumetric LiDar point cloud )
Super Fast and Accurate 3D Object Detection based on 3D LiDAR Point Clouds (The PyTorch implementation)
Convert KITTI dataset to ROS bag file the easy way!
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.
Surfel-based Mapping for 3d Laser Range Data (SuMa)
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)
3D Object Detection for Autonomous Driving: A Comprehensive Survey (IJCV 2023)
[3DV 2021] DSP-SLAM: Object Oriented SLAM with Deep Shape Priors
A 3D vision library from 2D keypoints: monocular and stereo 3D detection for humans, social distancing, and body orientation.
Tutorial for using Kitti dataset easily
📸 PyTorch implementation of MobileNetV3 for real-time semantic segmentation, with pretrained weights & state-of-the-art performance
Single Image Depth Estimation with Feature Pyramid Network
Convert between visual object detection datasets
Visualising LIDAR data from KITTI dataset.
Unofficial PyTorch implementation of "RTM3D: Real-time Monocular 3D Detection from Object Keypoints for Autonomous Driving" (ECCV 2020)
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
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