ECCV 2020 Workshop on

Adversarial Robustness in the Real World

Glasgow, Scotland
Aug 23, 2020


Computer vision systems nowadays have advanced performance but research in adversarial machine learning also shows that they are not as robust as the human vision system. The existence of real-world adversarial examples, created under scenarios such as partial occlusion or previously unseen environments, provides opportunities for understanding and improving computer vision systems.

We will award two TITAN RTX GPUs as prizes that were generously sponsored by NVIDIA.

Call For Papers

Submission deadline: June 4 July 10, 2020 Anywhere on Earth (AoE)

Reviews due: July 26, 2020 Anywhere on Earth (AoE)

Notification sent to authors: July 10 July 30, 2020 Anywhere on Earth (AoE)

Camera ready deadline: July 16 September 14, 2020 Anywhere on Earth (AoE)

Submission server:

Submission format: Submissions need to be anonymized and follow the ECCV 2020 Author Instructions. The workshop considers two types of submissions: (1) Long Paper: Papers are limited to 14 pages excluding references and will be included in the official ECCV proceedings; (2) Extended Abstract: Papers are limited to 7 pages excluding references and will NOT be included in the official ECCV proceedings. Based on the PC recommendations, the accepted long papers/extended abstracts will be allocated either a contributed talk or a poster presentation.

We invite submissions on any aspect of adversarial robustness in real-world computer vision. This includes, but is not limited to:




Organizing Committee

Program Committee



Please contact Adam Kortylewski or Cihang Xie if you have questions. The webpage template is by the courtesy of CVPR 2020 Workshop on Adversarial Machine Learning in Computer Vision.