ACCV 2016 Workshop on Interpretation and Visualization of Deep Neural Nets

Workshop at 13th Asian Conference on Computer Vision (ACCV’16)
Taipei International Convention Center (TICC), Taipei, Taiwan
24 November 2016
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Deep Neural Networks (DNNs) are known to excel in many fields, such as image recognition, object detection, video classification, machine translation, reinforcement learning among many others. While their results are impressive, DNNs often acts as a black box and do not provide detailed information about why they reaches a certain classification decision.

The Workshop on Interpretation and Visualization of Deep Neural Nets (WINVIZNN2016) encourages submissions related to interpretations, understanding and visualizations of predictions of deep neural nets. We are open about domains, be it theoretical papers which shed light on the success of deep neural nets or interpretation/visualization applications for deep neural nets on images, text documents and videos but also other domains such as audio signals. We welcome – yet are not restricted to - results about neural networks that explain decisions, that compare neural net models, and interpretation/ understanding results for novel application domains. The goal of this workshop is to foster collaboration and understanding on this emerging topic.

For more information see http://interpretable-ml.org/accv2016workshop

CALL FOR PAPERS
Submissions are required to stick to the ACCV format. Each paper should be at most 14 pages long — shorter papers are welcome, and be submitted into the conference management system. For accepted papers, at least one author must attend the workshop to present the work. The workshop will have an oral and a poster session.

Submission website: https://cmt3.research.microsoft.com/WINVIZNN2016