{"id":27403605,"url":"https://github.com/eloiz/awesome_explainable_driving","last_synced_at":"2026-01-24T03:08:24.013Z","repository":{"id":144843026,"uuid":"333367093","full_name":"EloiZ/awesome_explainable_driving","owner":"EloiZ","description":"A curated list of papers on explainability and interpretability of self-driving 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awesome_explainable_driving\nA curated list of papers on explainability and interpretability of self-driving models\n\nMost of the references below are organized and discuss in the following survey:\n* **Explainability of vision-based autonomous driving systems: Review and challenges** (submitted to IJCV), Eloi Zablocki, Hédi Ben-Younes, Patrick Pérez, Matthieu Cord [[arxiv]](https://arxiv.org/abs/2101.05307)\n\n\n## Table of Contents\n* [Saliency maps](#saliency-maps)\n* [Counterfactual interventions and causal inference](#counterfactual-interventions-and-causal-inference)\n* [Representation](#representation)\n* [Evaluation](#evaluation)\n* [Attention maps](#attention-maps)\n* [Semantic inputs](#semantic-inputs)\n* [Predicting intermediate representations](#predicting-intermediate-representations)\n* [Output interpretability](#output-interpretability)\n* [Natural language explanations](#natural-language-explanations)\n* [Datasets](#datasets)\n\n\n## Saliency maps\n\n* **Explaining How a Deep Neural Network Trained with End-to-End Learning Steers a Car** (2017, arxiv), Mariusz Bojarski, Philip Yeres, Anna Choromanska, Krzysztof Choromanski, Bernhard Firner, Lawrence Jackel, Urs Muller [[arxiv]](https://arxiv.org/abs/1704.07911)\n* **Visualbackprop: Efficient visualization of cnns for au-tonomous driving** (2018, ICRA), Mariusz Bojarski, Anna Choromanska, Krzysztof Choromanski, Bernhard Firner, Larry Jackel, Urs Muller, Karol Zieba [[arxiv]](https://arxiv.org/abs/1611.05418)\n* **Interpretable learning for self-driving cars by visualizing causal attention** (2017, ICCV), Jinkyu Kim, John Canny [[arxiv]](https://arxiv.org/abs/1703.10631)\n* **Conditional Affordance Learning for Driving in Urban Environments** (2018, CoRL), Axel Sauer, Nikolay Savinov, Andreas Geiger [[arxiv]](https://arxiv.org/abs/1806.06498)\n* **Interpretable Self-Attention Temporal Reasoning for Driving Behavior Understanding** (2020, ICASSP), Yi-Chieh Liu, Yung-An Hsieh, Min-Hung Chen, Chao-Han Huck Yang, Jesper Tegner, Yi-Chang James Tsai [[arxiv]](https://arxiv.org/abs/1911.02172)\n\n## Counterfactual interventions and causal inference\n\n* **Explaining How a Deep Neural Network Trained with End-to-End Learning Steers a Car** (2017, arxiv), Mariusz Bojarski, Philip Yeres, Anna Choromanska, Krzysztof Choromanski, Bernhard Firner, Lawrence Jackel, Urs Muller [[arxiv]](https://arxiv.org/abs/1704.07911)\n* **Who Make Drivers Stop? Towards Driver-centric Risk Assessment: Risk Object Identification via Causal Inference** (2020, IROS), Chengxi Li, Stanley H. Chan, Yi-Ting Chen [[arxiv]](https://arxiv.org/abs/2003.02425)\n* **ChauffeurNet: Learning to Drive by Imitating the Best and Synthesizing the Worst** (2019 Robotics, Science and Systems), Mayank Bansal, Alex Krizhevsky, Abhijit Ogale [[arxiv]](https://arxiv.org/abs/1812.03079)\n\n\n## Representation\n\n* **DeepTest: Automated Testing of Deep-Neural-Network-driven Autonomous Cars** (2018, ICSE), Yuchi Tian, Kexin Pei, Suman Jana, Baishakhi Ray [[arxiv]](https://arxiv.org/abs/1708.08559)\n\n## Evaluation\n\n* **ChauffeurNet: Learning to Drive by Imitating the Best and Synthesizing the Worst** (2019 Robotics, Science and Systems), Mayank Bansal, Alex Krizhevsky, Abhijit Ogale [[arxiv]](https://arxiv.org/abs/1812.03079)\n* **Learning Accurate and Human-Like Driving using Semantic Maps and Attention** (2020, IROS), Simon Hecker, Dengxin Dai, Alexander Liniger, Luc Van Gool [[arxiv]](https://arxiv.org/abs/2007.07218)\n* **DeepTest: Automated Testing of Deep-Neural-Network-driven Autonomous Cars** (2018, ICSE), Yuchi Tian, Kexin Pei, Suman Jana, Baishakhi Ray [[arxiv]](https://arxiv.org/abs/1708.08559)\n\n\n## Attention maps\n\n* **Interpretable learning for self-driving cars by visualizing causal attention** (2017, ICCV), Jinkyu Kim, John Canny [[arxiv]](https://arxiv.org/abs/1703.10631)\n* **Deep Object-Centric Policies for Autonomous Driving** (2019, ICRA), Dequan Wang, Coline Devin, Qi-Zhi Cai, Fisher Yu, Trevor Darrell [[arxiv]](https://arxiv.org/abs/1811.05432)\n* **Attentional Bottleneck: Towards an Interpretable Deep Driving Network** (2020, arxiv), Jinkyu Kim, Mayank Bansal [[arxiv]](https://arxiv.org/abs/2005.04298)\n* **Learning Accurate and Human-Like Driving using Semantic Maps and Attention** (2020, IROS), Simon Hecker, Dengxin Dai, Alexander Liniger, Luc Van Gool [[arxiv]](https://arxiv.org/abs/2007.07218)\n\n\n## Semantic inputs\n\n## Predicting intermediate representations\n\n## Output interpretability\n\n## Natural language explanations\n\n## Datasets\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Feloiz%2Fawesome_explainable_driving","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Feloiz%2Fawesome_explainable_driving","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Feloiz%2Fawesome_explainable_driving/lists"}