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SS-CAM: Smoothed Score-CAM for Sharper Visual Feature Localization

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arxiv 2006.14255 v3 pith:YN5XMAGA submitted 2020-06-25 cs.CV

Haofan Wang , Rakshit Naidu , Joy Michael , Soumya Snigdha Kundu This is my paper · ORCID
classification cs.CV
keywords localizationscore-camvisualdeepss-camanalyzedapplicationsapplied
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Interpretation of the underlying mechanisms of Deep Convolutional Neural Networks has become an important aspect of research in the field of deep learning due to their applications in high-risk environments. To explain these black-box architectures there have been many methods applied so the internal decisions can be analyzed and understood. In this paper, built on the top of Score-CAM, we introduce an enhanced visual explanation in terms of visual sharpness called SS-CAM, which produces centralized localization of object features within an image through a smooth operation. We evaluate our method on the ILSVRC 2012 Validation dataset, which outperforms Score-CAM on both faithfulness and localization tasks.

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Cited by 3 Pith papers

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