OFPNet is a baseline solution for Waymo Occupancy and Flow Prediction
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Updated
May 22, 2022 - Python
OFPNet is a baseline solution for Waymo Occupancy and Flow Prediction
NuScenes, Lyft, Waymo and a2d2 datasets parser.
3D object detection code for autonomous / tele-operated vehicles.
Analyze autonomous vehicles (AVs) user sentiment from online discussion forums to predict commercial adoption using news.
A toolkit for Waymo Open Dataset <-> KITTI conversions
Unlocking consistent interfacing to the most useful autonomous vehicle datasets and simulators.
Supporting Kits for generating waymo annotation files suitable for PIEPredict. Some files could still need manual data insertions.
Open Source Project for 3D Semantic Segmentation
🚫️📃️🚫️ An article on the problems with Google Waymo, and why you should stop using/avoid it.
Pedestrian Intention and Trajectory Prediction Study Using PIEPredict and LSTM Models over PIE and Waymo-Open datasets.
2D Object Detection on Waymo Open Dataset using Tensorflow
A toolkit for extracting elements and visualization for Waymo Open Dataset
Waymo Open Dataset: Tensorflow 2 Object Detection API
Submission for Waymo Open Dataset Challenge 2020 - 3D Tracking
PyTorch dataloader for Waymo Open Dataset
The repo of the preprinting paper "Labels Are Not Perfect: Inferring Spatial Uncertainty in Object Detection"
Course Submission Material for Resnet based object detection for Udacity Self Driving NanoDegree.
tool to convert waymo open dataset to rosbag
This project introduces the autonomous robot which is a scaled down version of actual self-driving vehicle and designed with the help of neural network. The main focus is on building autonomous robot and train it on a designed track with the help of neural network so that it can run autonomously without a controller or driver on that specific tr…
This repository provides awesome research papers for autonomous driving perception. If you do find a problem or have any suggestions, please raise this as an issue or make a pull request with information (format of the repo): Research paper title, datasets, metrics, objects, source code, publisher, and year.
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