Search Results for author: Ashkan Mokarian

Found 2 papers, 1 papers with code

How Shift Equivariance Impacts Metric Learning for Instance Segmentation

1 code implementation ICCV 2021 Josef Lorenz Rumberger, Xiaoyan Yu, Peter Hirsch, Melanie Dohmen, Vanessa Emanuela Guarino, Ashkan Mokarian, Lisa Mais, Jan Funke, Dagmar Kainmueller

In our work, we contribute a comprehensive formal analysis of the shift equivariance properties of encoder-decoder-style CNNs, which yields a clear picture of what can and cannot be achieved with metric learning in the face of same-looking objects.

Instance Segmentation Metric Learning +1

Mean Box Pooling: A Rich Image Representation and Output Embedding for the Visual Madlibs Task

no code implementations9 Aug 2016 Ashkan Mokarian, Mateusz Malinowski, Mario Fritz

We present Mean Box Pooling, a novel visual representation that pools over CNN representations of a large number, highly overlapping object proposals.

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