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@ -198,6 +198,7 @@ This is an on-going attempt to consolidate interesting efforts in the area of un
* BiLRP: Building and Interpreting Deep Similarity Models. _Jie Zhou et al. TPAMI 2020_ [pdf](https://arxiv.org/abs/2003.05431 "LRP applied to image matching models")
* SANE: Why do These Match? Explaining the Behavior of Image Similarity Models. _Plummer et al. ECCV 2020_ [pdf](https://arxiv.org/abs/1905.10797 "Matching saliency maps to discrete attributes for specific applications for clothes recommendation")
* Visualizing Deep Similarity Networks. _Stylianou et al. WACV 2019_ [pdf](https://arxiv.org/abs/1901.00536 "Factoring the dot product of two Siamese branches into two heatmaps, each for a branch.") | [code](https://github.com/GWUvision/Similarity-Visualization)
* Visual Explanation for Deep Metric Learning. _Zhu et al. 2019_ [pdf](https://arxiv.org/abs/1909.12977 "Taking dot product between a patch in image A with every patch in image B to compute a weakly-supervised correspondence map") | [code](https://github.com/Jeff-Zilence/Explain_Metric_Learning)
#### Face verification
* DISE: Explainable Face Recognition. _Williford et al. ECCV 2020_ [pdf](https://arxiv.org/abs/2008.00916 "Extension of RISE in face-matching. Mask out a small region in the query image to compute its attribution to the image-matching triplet loss") | [code](https://github.com/stresearch/xfr)