Master’s Thesis Presentation • Artificial Intelligence — Towards Pixel-Level OOD Detection for Semantic SegmentationExport this event to calendar

Tuesday, July 23, 2019 — 11:30 AM EDT

Matthew Angus, Master’s candidate
David R. Cheriton School of Computer Science

There exists wide research surrounding the detection of out of distribution sample for image classification. Safety critical applications, such as autonomous driving, would benefit from the ability to localise the unusual objects causing an image to be out of distribution. 

This paper adapts state-of-the-art methods for detecting out of distribution images for image classification to the new task of detecting out of distribution pixels, which can localise the unusual objects. It further experimentally compares the adapted methods to a new dataset derived from existing semantic segmentation datasets, proposing a new metric for the task. The evaluation shows that the performance ranking of the compared methods successfully transfers to the new task.

Location 
DC - William G. Davis Computer Research Centre
2310
200 University Avenue West

Waterloo, ON N2L 3G1
Canada

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