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