BMVC 2019 Workshop

Interpretable & Explainable Machine Vision

September 12th 2019 at bmvc2019.org

Recent years have seen significant advances in techniques for image processing and machine vision based on breakthroughs in machine learning and artificial intelligence, especially in the area of deep neural networks. However, such techniques are widely viewed as creating “black box” systems that are in some senses “inscrutable”, leading to concerns over their reliability, stability, and trustworthiness. Consequently, we have seen a surge of interest in approaches aimed at “opening the black boxes” commonly characterised by the terms interpretability and explainability.

Topics

Topics of interest include (but are not limited to):

  • Improving the theoretical basis of interpretability and explainability techniques
  • Practical interpretability and explainability techniques for system developers
  • Case studies of applied interpretability and explainability approaches
  • Visualisation techniques for network layer representations
  • Evaluation metrics for interpretability
  • Psychological and human-in-the-loop perspectives on interpretability and explainability
  • Approaches aimed at assuring fairness, accountability and transparency
  • Interpretable model architectures
  • Explaining and interpreting uncertainty

Submissions

We welcome either full papers (up to 9 pages) or short papers (4 pages) that we will select either for presentation or as posters. All submissions should follow the BMVC conference style. We particularly encourage PhD student-led submissions.

The workshop CMT submission site will open soon.

Dates

Submission (long and short papers): Monday July 1st 2019

Acceptance notification: Monday July 29th 2019

Final ‘camera-ready’ versions: Monday August 12th 2019

Programme outline

  • Invited talk
  • Paper session 1
  • Poster “trailers”
  • Break / poster session
  • Paper session 2

Organising Committee

  • Alun Preece (Cardiff University, UK) - primary contact
  • Supriyo Chakraborty (IBM Research, USA)
  • Lewis Griffin (UCL)
  • Mark Hall (Airbus, UK)
  • Simon Julier (UCL)
  • Richard Tomsett (IBM Research, UK)
  • Sriram Varadarajan (BAE Systems, UK)
  • Chris Willis (BAE Systems, UK)