Train a Fully Convolutional Network to find roads from images!
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Updated
Oct 29, 2017 - Python
Train a Fully Convolutional Network to find roads from images!
PyTorch implementation for 3D Bounding Box Estimation Using Deep Learning and Geometry
Code for the Didi/Udacity SDC Challenge 2017
Deep3DBox's MXNet implementation. (In Progress: %95)
Detect object in 3D with Point Cloud and Image.
Tutorial for using Kitti dataset easily
Dataset tools for working with the KITTI dataset raw data ( http://www.cvlibs.net/datasets/kitti/raw_data.php ) and converting it to a ROS bag. Also allows a library for direct access to poses, velodyne scans, and images.
Segment lanes on KITTI
Nearest neighbor depth completion
A two stage multi-modal loss model along with rigid body transformations to regress 3D bounding boxes
AVOD needs the planes file to provide ground plane information, but the official planes generation tool has not yet been provided, which brings great difficulty to the test work. This project is used to generate planes files especially for AVOD testing.
An Evaluation Metric for Object Detection Algorithms in Autonomous Navigation Systems and its application to a real-time alerting system
Python-based optical flow toolkit for existing popular dataset
VoxelNet Implementation for Usage on Win and Linux Systems
Implementation of "Boosting LiDAR-based Semantic Labeling by Cross-Modal Training Data Generation"
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