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. Accepted papers will appear in the CVPR workshop proceedings. 

Submission Deadline: March 10,  Anywhere on Earth (UTC-12) 

Extended Submission Deadline: March 16,  Anywhere on Earth (UTC-12) 

Author Notification: April 1

Camera ready due: April 6

Submission via CMT: https://cmt3.research.microsoft.com/SAIAD2023/

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.

• Abhishek Vivekanandan, FZI

• Ahmed Hammam, Opel Automobile GmbH

• Andrea Kraus, Valeo

• Andreas Bär, TUB

• Benedict Stephan, TU-Ilmenau

• Benjamin Hartmann, Siemens Mobility

• Christian Wojek, Zeiss Research

• Christof Hoppe, Siemens Mobility

• Claus Bahlmann, Siemens Mobility

• Daniel Bogdoll, FZI

• Federico Becattini, Università di Firenze

• Gesina Schwalbe, Continental

• Hanno Gottschalk, University of Wuppertal

• Irina Vidal Migallón, Siemens Mobility GmbH

• Jasmin Breitenstein, Technische Universität Braunschweig

• Joachim Sicking, Fraunhofer

• Karl Amende, Valeo

• Karsten Roscher, Frauenhofer IKS

• Konrad Groh, Bosch

• Krystian Radlak, Warsaw University of Technology

• Mahmoud Salem, KIT

• Markus Enzweiler, University of Applied Sciences Esslingen

• Martin Simon, Valeo

• Matthias Rottmann, University of Wuppertal

• Naveen Shankar Nagaraja, BMW Group

• Oliver Wasenmüller, University of Applied Sciences Mannheim

• Peter Schlicht, Cariad

• Phillip Heidenreich, Opel

• Praneet Dutta, DeepMind, Google AI

• Ravi Kiran, Navya

• René Schuster, DFKI

• Sebastian Schulze, Merantix

• Senthil Yogamani, Qualcomm

• Shyam Nandan Rai, Politecnico di Torino

• Stefan Milz, Spleenlab.ai / Ilmenau University

• Thomas Stauner, BMW AG

• Tim Fingscheidt, Technische Universität Braunschweig

• Timo Sämann, Valeo