RL and distillation in CARLA using a factorized world model

Overview

World on Rails

teaser

Learning to drive from a world on rails
Dian Chen, Vladlen Koltun, Philipp Krähenbühl,
arXiv techical report (arXiv 2105.00636)

PWC

This repo contains code for our paper Learning to drive from a world on rails.

ProcGen code coming soon.

Reference

If you find our repo or paper useful, please cite us as

@inproceedings{chen2021learning,
  title={Learning to drive from a world on rails},
  author={Chen, Dian and Koltun, Vladlen and Kr{\"a}henb{\"u}hl, Philipp},
  booktitle={arXiv preprint arXiv:2105.00636},
  year={2021}
}

Updates

  • Checkout our website for demo videos!

Getting Started

  • To run CARLA and train the models, make sure you are using a machine with at least a mid-end GPU.
  • Please follow INSTALL.md to setup the environment.

Training

  • Please refer to RAILS.md on how to train our World-on-Rails agent.
  • Please refer to LBC.md on how to train the LBC agent.

Evaluation

Leaderboard routes

python evaluate.py --agent-config=[PATH TO CONFIG]

NoCrash routes

python evaluate_nocrash.py --town={Town01,Town02} --weather={train, test} --agent-config=[PATH TO CONFIG] --resume
  • Use defaults for RAILS, and --agent=autoagents/lbc_agent for LBC.
  • To print a readable table, use
python -m scripts.view_nocrash_results [PATH TO CONFIG.YAML]

Pretrained weights

Dataset

We also release the data we trained for the leaderboard. Checkout DATASET.md for more details.

Acknowledgements

The leaderboard codes are built from the original leaderboard repo. The scenariorunner codes are from the original scenario_runner repo. The waypointer.py GPS coordinate conversion codes are build from Marin Toromanoff's leadeboard submission.

License

This repo is released under the MIT License (please refer to the LICENSE file for details). The leaderboard repo which our leaderboard folder builds upon is under the MIT License.

Cascaded Deep Video Deblurring Using Temporal Sharpness Prior and Non-local Spatial-Temporal Similarity

This repository is the official PyTorch implementation of Cascaded Deep Video Deblurring Using Temporal Sharpness Prior and Non-local Spatial-Temporal Similarity

hippopmonkey 4 Dec 11, 2022
Flexible Option Learning - NeurIPS 2021

Flexible Option Learning This repository contains code for the paper Flexible Option Learning presented as a Spotlight at NeurIPS 2021. The implementa

Martin Klissarov 7 Nov 09, 2022
Official implementation of "UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-wise Perspective with Transformer"

[AAAI2022] UCTransNet This repo is the official implementation of "UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-wise Perspectiv

Haonan Wang 199 Jan 03, 2023
PyTorch implementation of "Representing Shape Collections with Alignment-Aware Linear Models" paper.

deep-linear-shapes PyTorch implementation of "Representing Shape Collections with Alignment-Aware Linear Models" paper. If you find this code useful i

Romain Loiseau 27 Sep 24, 2022
Companion code for the paper Theoretical characterization of uncertainty in high-dimensional linear classification

Companion code for the paper Theoretical characterization of uncertainty in high-dimensional linear classification Usage The required packages are lis

0 Feb 07, 2022
'Solving the sampling problem of the Sycamore quantum supremacy circuits

solve_sycamore This repo contains data, contraction code, and contraction order for the paper ''Solving the sampling problem of the Sycamore quantum s

Feng Pan 29 Nov 28, 2022
Transport Mode detection - can detect the mode of transport with the help of features such as acceeration,jerk etc

title emoji colorFrom colorTo sdk app_file pinned Transport_Mode_Detector 🚀 purple yellow gradio app.py false Configuration title: string Display tit

Nishant Rajadhyaksha 3 Jan 16, 2022
A PyTorch implementation of NeRF (Neural Radiance Fields) that reproduces the results.

NeRF-pytorch NeRF (Neural Radiance Fields) is a method that achieves state-of-the-art results for synthesizing novel views of complex scenes. Here are

Yen-Chen Lin 3.2k Jan 08, 2023
X-modaler is a versatile and high-performance codebase for cross-modal analytics.

X-modaler X-modaler is a versatile and high-performance codebase for cross-modal analytics. This codebase unifies comprehensive high-quality modules i

910 Dec 28, 2022
Generic Event Boundary Detection: A Benchmark for Event Segmentation

Generic Event Boundary Detection: A Benchmark for Event Segmentation We release our data annotation & baseline codes for detecting generic event bound

47 Nov 22, 2022
Program your own vulkan.gpuinfo.org query in Python. Used to determine baseline hardware for WebGPU.

query-gpuinfo-data License This software is not presently released under a license. The data in data/ is obtained under CC BY 4.0 as specified there.

Kai Ninomiya 5 Jul 18, 2022
Codecov coverage standard for Python

Python-Standard Last Updated: 01/07/22 00:09:25 What is this? This is a Python application, with basic unit tests, for which coverage is uploaded to C

Codecov 10 Nov 04, 2022
This is the official pytorch implementation of Student Helping Teacher: Teacher Evolution via Self-Knowledge Distillation(TESKD)

Student Helping Teacher: Teacher Evolution via Self-Knowledge Distillation (TESKD) By Zheng Li[1,4], Xiang Li[2], Lingfeng Yang[2,4], Jian Yang[2], Zh

Zheng Li 9 Sep 26, 2022
Neural Turing Machine (NTM) & Differentiable Neural Computer (DNC) with pytorch & visdom

Neural Turing Machine (NTM) & Differentiable Neural Computer (DNC) with pytorch & visdom Sample on-line plotting while training(avg loss)/testing(writ

Jingwei Zhang 269 Nov 15, 2022
Patient-Survival - Using Python, I developed a Machine Learning model using classification techniques such as Random Forest and SVM classifiers to predict a patient's survival status that have undergone breast cancer surgery.

Patient-Survival - Using Python, I developed a Machine Learning model using classification techniques such as Random Forest and SVM classifiers to predict a patient's survival status that have underg

Nafis Ahmed 1 Dec 28, 2021
Awesome Monocular 3D detection

Awesome Monocular 3D detection Paper list of 3D detetction, keep updating! Contents Paper List 2022 2021 2020 2019 2018 2017 2016 KITTI Results Paper

Zhikang Zou 184 Jan 04, 2023
code for Fast Point Cloud Registration with Optimal Transport

robot This is the repository for the paper "Accurate Point Cloud Registration with Robust Optimal Transport". We are in the process of refactoring the

28 Jan 04, 2023
Unsupervised captioning - Code for Unsupervised Image Captioning

Unsupervised Image Captioning by Yang Feng, Lin Ma, Wei Liu, and Jiebo Luo Introduction Most image captioning models are trained using paired image-se

Yang Feng 207 Dec 24, 2022
Disentangled Lifespan Face Synthesis

Disentangled Lifespan Face Synthesis Project Page | Paper Demo on Colab Preparation Please follow this github to prepare the environments and dataset.

何森 50 Sep 20, 2022
这是一个利用facenet和retinaface实现人脸识别的库,可以进行在线的人脸识别。

Facenet+Retinaface:人脸识别模型在Keras当中的实现 目录 注意事项 Attention 所需环境 Environment 文件下载 Download 预测步骤 How2predict 参考资料 Reference 注意事项 该库中包含了两个网络,分别是retinaface和fa

Bubbliiiing 31 Nov 15, 2022