Recent deep-learning-based methods achieve great performance on various vision applications. However, insufficient robustness on adversarial cases limits real-world applications of deep-learning-based methods. AROW workshop aims to explore adversarial examples, as well as, evaluate and improve the adversarial robustness of computer vision systems.

This AROW workshop will be fully virtual.

Topics of AROW workshop include but are not limited to:

  • Improving model robustness against unrestricted adversarial attacks
  • Improving generalization to out-of-distribution samples or unforeseen adversaries
  • Discovery of real-world adversarial examples
  • Novel architectures with robustness to occlusion, viewpoint, and other real-world domain shifts
  • Domain adaptation techniques for robust vision in the real world
  • Datasets for evaluating model robustness
  • Structured deep models and explainable AI

  • Schedule

    Oct. 23, 2022. IST: Israel local time (UTC +2); PST: Pacific Standard Time (UTC -8) Live

    Israel Morning Session

  • PST 11:05pm-11:35pm; IST 9:05am-9:35am
  • Invited Talk: Cihang Xie - CNN vs Transformer: Which One is More Robust - Live

  • PST 11:35pm-12:05am; IST 9:35am-10:05am
  • Invited Talk: Olga Russakovsky - Trustworthy and trusted computer vision

  • PST 12:05am-12:35am; IST 10:05am-10:35am
  • Invited Talk: Alan Yuille - Challenging Artificial Intellegence of Vision Algorithm to Achieve Human-Level Performance

  • PST 12:35am-1:05am; IST 10:35am-11:05am
  • Invited Talk: Xue Lin - Evaluation of Deep Learning Robustness and Reverse Engineering of Pertubations

    Israel Afternoon Session

  • PST 4:15am-5:00am; IST 2:15pm-3:00pm
  • Invited Talk: Hima Hlakkaraju - Bringing Order to Chaos: Probing the Disagreement Problem in Explainable AI

  • PST 5:00am-5:45am; IST 3:00pm-3:45pm
  • Invited Talk: Pin-Yu Chen - Reprogramming Foundation Models with Limited Resources - Live

  • PST 5:45am-6:30am; IST 3:45pm-4:30pm
  • Invited Talk: Ekin Dogus Cubuk - Adversarial examples of classifiers, physical systems, and beyond - Live

  • PST 6:30am-7:00am; IST 4:30pm-5:00pm
  • Invited Talk: Bolei Zhou - Benchmarking AI Safety of Autonomous Driving through Diverse Traffic Scenario Generation - Live

  • PST 7:00am-7:30am; IST 5:00pm-5:30pm
  • Invited Talk: Dan Hendrycks - Beyond the Lp Ball and Long Tails - Live

  • PST 7:30am-8:30am; IST 5:30pm-6:30pm
  • Best Paper Session - Live

    Best Paper Awards

    AROW Workshop Best Papers

  • Physical Passive Patch Adversarial Attacks on Visual Odometry Systems [Paper] [Supp]
    Yaniv Nemcovsky (Technion); Matan Jacoby (Technion); Alex Bronstein (Tel Aviv University, Israel); Chaim Baskin (Technion)*
  • FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning [Paper]
    Kaiyuan Zhang (Purdue University)*; Guanhong Tao (Purdue University); Qiuling Xu (Purdue University); Siyuan Cheng (Purdue University); Shengwei An (Purdue University); Yingqi Liu (Purdue University); Shiwei Feng (Purdue University); Pin-Yu Chen (IBM Research); Shiqing Ma (Rutgers University); Xiangyu Zhang (Purdue University)
  • Best Papers

  • ALA: Adversarial Lightness Attack via Naturalness-aware Regularizations [Paper]
    Liangru Sun (East China Normal University)*; Felix Juefei-Xu (Meta AI); Yihao Huang (East China Normal University); Qing Guo (Nanyang Technological University); Jiayi Zhu (East China Normal University); Jincao Feng (East China Normal University); Yang Liu (Nanyang Technology University, Singapore); Geguang Pu (East China Normal University)
  • Attacking Motion Estimation with Adversarial Snow [Paper] [Supp]
    Jenny Schmalfuss (University of Stuttgart)*; Lukas Mehl (University of Stuttgart); Andrés Bruhn (University of Stuttgart)
  • BadDet: Backdoor Attacks on Object Detection [Paper]
    Shih-Han Chan (University of California San Diego)*; Yinpeng Dong (Tsinghua University); Jun Zhu (Tsinghua University); Xiaolu Zhang (Ant Financial Services Group); Jun Zhou (Ant Financial)

  • Accepted Long Paper

    Accepted Extended Abstract


    Hima Lakkaraju
    Harvard University
    Olga Russakovsky
    Princeton University
    Cihang Xie
    Alan Yuille
    Johns Hopkins University

    Organizing Committee

    Program Committee

    • Akshayvarun Subramanya (UMBC)
    • Alexander Robey (University of Pennsylvania)
    • Cheng Xinwen (Shanghai JiaoTong University)
    • Dingcheng Yang (Tsinghua University)
    • Gaurang Sriramanan (UMD)
    • Guofeng Zhang (UCLA)
    • Hanxun Huang (The University of Melbourne)
    • Jiachen Sun (University of Michigan)
    • Jieru Mei (Johns Hopkins University)
    • Junbo Li (UC Santa Cruz)
    • Kibok Lee (Yonsei University)
    • Lifeng Huang (SunYat-sen university)
    • Maura Pintor (University of Cagliari)
    • Nataniel Ruiz (Boston University)
    • Pengliang Ji (Beihang University)
    • Qihao Liu (Johns Hopkins University)
    • Qing Jin (Northeastern University)
    • Rajkumar Theagarajan (UC Riverside)
    • Ruihao Gong (SenseTime)
    • Salah GHAMIZI (University of Luxembourg)
    • Shihao Zhao (The University of Hong Kong)
    • Shunchang liu (Beihang University)
    • Shutong Wu (Shanghai Jiao Tong University)
    • Sizhe Chen (Shanghai Jiao Tong University)
    • Sravanti Addepalli (Indian Institute of Science)
    • Tao Li (Shanghai Jiao Tong University)
    • Tianlin Li (NTU)
    • Wenxiao Wang (University of Maryland)
    • Won Park (University of Michigan)
    • Wufei Ma (Johns Hopkins University)
    • Xiaoding Yuan (Johns Hopkins University)
    • Xingjun Ma (Fudan University)
    • Yige Li (Xidian University)
    • Yue Wang (Ford Motor Company)
    • Yulong Cao (University of Michigan)
    • Zhehao Huang (Shanghai Jiao Tong University)
    • Zhengyi Wang (Tsinghua University)
    • Zhongkai Hao (Tsinghua University)
    • Zhouxing Shi (UCLA)
    • Zichao Li (UC Santa Cruz)
    • Zihao Xiao (Johns Hopkins University)
    • Zonglei Jing (Beihang University)


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    Please contact Angtian Wang or Yutong Bai if you have questions. The webpage template is by the courtesy of ECCV 2020 Workshop on Adversarial Robustness in the Real World.