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HIVE: Evaluating the Human Interpretability of Visual Explanations


Jan 10, 2022
Sunnie S. Y. Kim, Nicole Meister, Vikram V. Ramaswamy, Ruth Fong, Olga Russakovsky

* HIVE can be found at https://princetonvisualai.github.io/HIVE 

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Debiasing Convolutional Neural Networks via Meta Orthogonalization


Nov 15, 2020
Kurtis Evan David, Qiang Liu, Ruth Fong

* Accepted to NeuRIPS 2020 Workshop on Algorithmic Fairness through the Lens of Causality and Interpretability (AFCI). Supplemental materials provided at: https://drive.google.com/drive/folders/1klIAqZDgg3sCVmzFjLw5Y_T-GTc2E3oh?usp=sharing 

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Contextual Semantic Interpretability


Sep 18, 2020
Diego Marcos, Ruth Fong, Sylvain Lobry, Remi Flamary, Nicolas Courty, Devis Tuia

* ACCV 2020 

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There and Back Again: Revisiting Backpropagation Saliency Methods


Apr 06, 2020
Sylvestre-Alvise Rebuffi, Ruth Fong, Xu Ji, Andrea Vedaldi

* CVPR 2020 

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Multi-modal Self-Supervision from Generalized Data Transformations


Mar 09, 2020
Mandela Patrick, Yuki M. Asano, Ruth Fong, João F. Henriques, Geoffrey Zweig, Andrea Vedaldi


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Occlusions for Effective Data Augmentation in Image Classification


Oct 25, 2019
Ruth Fong, Andrea Vedaldi

* Accepted to 2019 ICCV Workshop on Interpreting and Explaining Visual Artificial Intelligence Models (v2: corrected references) 

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NormGrad: Finding the Pixels that Matter for Training


Oct 19, 2019
Sylvestre-Alvise Rebuffi, Ruth Fong, Xu Ji, Hakan Bilen, Andrea Vedaldi


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Understanding Deep Networks via Extremal Perturbations and Smooth Masks


Oct 18, 2019
Ruth Fong, Mandela Patrick, Andrea Vedaldi

* Accepted at ICCV 2019 as oral; supp mat at http://ruthcfong.github.io/files/fong19_extremal_supps.pdf 

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Net2Vec: Quantifying and Explaining how Concepts are Encoded by Filters in Deep Neural Networks


Mar 29, 2018
Ruth Fong, Andrea Vedaldi

* Camera-Ready for CVPR18; supplementary materials: http://ruthcfong.github.io/files/net2vec_supps.pdf 

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Interpretable Explanations of Black Boxes by Meaningful Perturbation


Jan 10, 2018
Ruth Fong, Andrea Vedaldi

* Proceedings of the 2017 IEEE International Conference on Computer Vision (ICCV) 
* Final camera-ready paper published at ICCV 2017 (Supplementary materials: http://openaccess.thecvf.com/content_ICCV_2017/supplemental/Fong_Interpretable_Explanations_of_ICCV_2017_supplemental.pdf

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Using Human Brain Activity to Guide Machine Learning


Sep 19, 2017
Ruth Fong, Walter Scheirer, David Cox

* Supplemental material can be downloaded here: http://www.wjscheirer.com/misc/activity_weights/fong-et-al-supplementary.pdf 

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