Accepted papers will be published in IEEE Xplore!

We award the best paper with the SAIAD best Paper Award!

Call for Papers

We are soliciting high quality papers covering the topics listed below. Papers should follow the standard CVPR formatting instructions. Paper length should be 4 to 8 pages according to the CVPR format. Accepted papers will appear in the CVPR workshop proceedings.

Submission Deadline: March 15, 2021, Anywhere on Earth (UTC-12)

Extended Submission Deadline: March 24, 2021, Anywhere on Earth (UTC-12)

Author Notification: April 7, 2021

Camera ready due: April 16, 2021

Submission via CMT: https://cmt3.research.microsoft.com/SAIAD2021

Topics of Interest

The topics of interest include (but are not limited to):

  • Interpretable and explainable Deep Neural Networks

  • Standardization in Safe AI

  • Ethics and legal aspects in Safe AI

  • Safe Deep Neural Network design

  • Certification of DNNs

  • Detection of out-of-distribution data

  • Robustness to anomalies / out-of-distribution data / adversarial examples

  • Uncertainty modeling

  • Transparent DNN training

  • Integrating legal requirements

  • Novel evaluation schemes


We follow a high quality review process with a notable Program Comittee.


  • Andrea Kraus, Valeo

  • Andreas Tamke, Bosch

  • Andreas Looft, Volkswagen car.SW Org

  • Claudia Blaiotta, Bosch

  • Felix Friedmann, Incenda / NVIDIA

  • Frank Hafner, ZF Friedrichshafen AG

  • Hanno Gottschalk, University of Wuppertal

  • Julian Kooij, TU Delft

  • Johannes Niedermayer, BMW

  • Karl Amende, Valeo

  • Konrad Groh, Bosch

  • Linara Adilova, Fraunhofer IAIS

  • Mark Schutera, ZF Friedrichshafen AG

  • Martin Simon, Valeo

  • Mohammed-Ali Mahani Nikouei, BMW

  • Nico Schmidt, Volkswagen car.SW Org

  • Naveen Shankar Nagaraja, BMW Group

  • Omesh Tickoo, Intel USA

  • Patrick Mäder, TU Ilmenau

  • Peter Pinggera, TensorEye

  • Philipp Heidenreich, Opel

  • Praneet Dutta, DeepMind

  • Qing Rao, BMW AG

  • René Schuster, DFKI

  • Senthil Yogamani, Valeo Vision Systems

  • Stefan Rüping, Fraunhofer IAIS

  • Stefan Wrobel, Uni Bonn

  • Stephanie Jonkers, Volkswagen car.SW Org

  • Thao Dang, HS Esslingen

  • Xavier Perrotton, Valeo

  • Xinshuo Weng, CMU

  • Yevgeniya Filippovska, Volkswagen car.SW Org


Topics of interest include (but are not limited to) :


  • Interpretable and explainable Deep Neural Networks

  • Safe Deep Neural Network design

  • Approximation of Deep Neural Networks

  • Evaluation of diagnostic techniques

  • Robustness to anomalies

  • Uncertainty modeling

  • Methods for meta classification

  • Transparent DNN training

  • Training Deep Networks

  • Integrating legal requirements

  • Novel evaluation schemes