Dawid Rymarczyk
ABSTRACT
In this work, we introduce an extension to ProtoPNet called ProtoPShare which shares prototypical parts between classes. To obtain prototype sharing we prune prototypical parts using a novel data-dependent similarity. Our approach substantially reduces the number of prototypes needed to preserve baseline accuracy and finds prototypical similarities between classes. We show the effectiveness of ProtoPShare on the CUB-200-2011 and the Stanford Cars datasets and confirm the semantic consistency of its prototypical parts in user-study.
Supplemental Material
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Index Terms
- ProtoPShare: Prototypical Parts Sharing for Similarity Discovery in Interpretable Image Classification
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