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

• URL: http://arxiv.org/abs/2006.14255v3
• Date: Thu, 12 Nov 2020 13:02:55 GMT
• Title: SS-CAM: Smoothed Score-CAM for Sharper Visual Feature Localization
• Authors: Haofan Wang, Rakshit Naidu, Joy Michael and Soumya Snigdha Kundu
• Abstract summary: We introduce an enhanced visual explanation in terms of visual sharpness called SS-CAM. We evaluate our method on the ILSVRC 2012 Validation dataset, which outperforms Score-CAM on both faithfulness and localization tasks.
• Score: 1.3381749415517021
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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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