Important Dates

Call for Papers

Deep learning has achieved significant success in multimedia fields, however research in adversarial learning also shows that it is highly vulnerable to adversarial examples. We invite submissions on any aspect of adversarial machine learning in multimedia deep learning systems. Topics include but not limited to:
  • Adversarial attacking deep learning systems
  • Robust architectures against adversarial attacks
  • Training techniques for building robust deep learning systems
  • Benchmark for evaluating model robustness
  • Understanding the adversarial vulnerabilities of deep learning systems
  • Improving generalization performance of computer vision systems to out-of-distribution samples
  • Explainable AI

Paper Submission

Format: Submitted papers (.pdf format) must use the ACM Article Template Please remember to add Concepts and Keywords.
Length: As stated in the CfP, submitted papers may be 6 to 8 pages. Up to two additional pages may be added for references. The reference pages must only contain references. Overlength papers will be rejected without review.
Submission Site: .