Cascading Unknown Detection with Known Classification for Open Set Recognition
Published in International Conference on Image Processing, 2024
Recommended citation: Brignac, Daniel and Mahalanobis, Abhijit, "Cascading Unknown Detection with Known Classification for Open Set Recognition,"2024 International Conference on Image Processing.
Deep learners tend to perform well when trained under the closed set assumption but struggle when deployed under open set conditions. This motivates the field of Open Set Recognition (OSR) in which we seek to give deep learners the ability to recognize whether a data sample belongs to the known classes trained on or comes from the surrounding infinite world. In this work, we decompose the traditional OSR formulation into fine class distinction and known/unknown class discrimination.