Explainability of Deep Vision-Based Autonomous Driving Systems: Review and Challenges

Author:

Zablocki ÉloiORCID,Ben-Younes Hédi,Pérez Patrick,Cord Matthieu

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Reference229 articles.

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2. Adebayo, J., Gilmer, J., Muelly, M., Goodfellow, IJ., Hardt, M., & Kim, B. (2018). Sanity checks for saliency maps. In NeurIPS

3. Agrawal, A., Batra, D., Parikh, D., & Kembhavi, A. (2018). Don’t just assume; look and answer: Overcoming priors for visual question answering. In CVPR

4. Agrawal, A., Lu, J., Antol, S., Mitchell, M., Zitnick, CL., Parikh, D., & Batra, D. (2017). VQA: visual question answering - www.visualqa.org. IJCV

5. Alhaija, HA., Mustikovela, SK., Mescheder, LM., Geiger, A., & Rother, C. (2018). Augmented reality meets computer vision: Efficient data generation for urban driving scenes. IJCV

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