Understanding Deep Networks via Extremal Perturbations and Smooth Masks

18 October 2019

Andrea Vedaldi

Papers citing "Understanding Deep Networks via Extremal Perturbations and Smooth Masks"

35 / 35 papers shown

Title
Soft-CAM: Making black box models self-explainable for high-stakes decisions K. Djoumessi Philipp Berens FAtt BDL 229 0 0 23 May 2025
Model Lakes Koyena Pal David Bau Renée J. Miller 155 2 0 24 Feb 2025
Generating visual explanations from deep networks using implicit neural representations Michal Byra Henrik Skibbe GAN FAtt 99 0 0 20 Jan 2025
Interpreting Low-level Vision Models with Causal Effect Maps Jinfan Hu Jinjin Gu Shiyao Yu Fanghua Yu Zheyuan Li Zhiyuan You Chaochao Lu Chao Dong CML 189 3 0 29 Jul 2024
Multiple Different Black Box Explanations for Image Classifiers Hana Chockler D. A. Kelly Daniel Kroening FAtt 79 0 0 25 Sep 2023
Interpretability-Aware Vision Transformer Yao Qiang Chengyin Li Prashant Khanduri D. Zhu ViT 237 8 0 14 Sep 2023
VISTANet: VIsual Spoken Textual Additive Net for Interpretable Multimodal Emotion Recognition Puneet Kumar Sarthak Malik Balasubramanian Raman Xiaobai Li 123 2 0 24 Aug 2022
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications Wojciech Samek G. Montavon Sebastian Lapuschkin Christopher J. Anders K. Müller XAI 114 83 0 17 Mar 2020
Sanity Checks for Saliency Maps Julius Adebayo Justin Gilmer M. Muelly Ian Goodfellow Moritz Hardt Been Kim FAtt AAML XAI 150 1,970 0 08 Oct 2018
RISE: Randomized Input Sampling for Explanation of Black-box Models Vitali Petsiuk Abir Das Kate Saenko FAtt 181 1,176 0 19 Jun 2018
Revisiting the Importance of Individual Units in CNNs via Ablation Bolei Zhou Yiyou Sun David Bau Antonio Torralba FAtt 111 117 0 07 Jun 2018
Constrained-CNN losses for weakly supervised segmentation H. Kervadec Jose Dolz Meng Tang Eric Granger Yuri Boykov Ismail Ben Ayed 76 240 0 12 May 2018
Net2Vec: Quantifying and Explaining how Concepts are Encoded by Filters in Deep Neural Networks Ruth C. Fong Andrea Vedaldi FAtt 80 264 0 10 Jan 2018
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV) Been Kim Martin Wattenberg Justin Gilmer Carrie J. Cai James Wexler F. Viégas Rory Sayres FAtt 232 1,850 0 30 Nov 2017
Deep Image Prior Dmitry Ulyanov Andrea Vedaldi Victor Lempitsky SupR 130 3,166 0 29 Nov 2017
SmoothGrad: removing noise by adding noise D. Smilkov Nikhil Thorat Been Kim F. Viégas Martin Wattenberg FAtt ODL 207 2,235 0 12 Jun 2017
Real Time Image Saliency for Black Box Classifiers P. Dabkowski Y. Gal 70 593 0 22 May 2017
Network Dissection: Quantifying Interpretability of Deep Visual Representations David Bau Bolei Zhou A. Khosla A. Oliva Antonio Torralba MILM FAtt 158 1,523 1 19 Apr 2017
Hide-and-Seek: Forcing a Network to be Meticulous for Weakly-supervised Object and Action Localization Krishna Kumar Singh Yong Jae Lee 93 682 0 13 Apr 2017
A-Fast-RCNN: Hard Positive Generation via Adversary for Object Detection Xinyu Wang Abhinav Shrivastava Abhinav Gupta ObjD 97 572 0 11 Apr 2017
Interpretable Explanations of Black Boxes by Meaningful Perturbation Ruth C. Fong Andrea Vedaldi FAtt AAML 76 1,525 0 11 Apr 2017
Object Region Mining with Adversarial Erasing: A Simple Classification to Semantic Segmentation Approach Yunchao Wei Jiashi Feng Xiaodan Liang Ming-Ming Cheng Yao-Min Zhao Shuicheng Yan 90 811 0 24 Mar 2017
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization Ramprasaath R. Selvaraju Michael Cogswell Abhishek Das Ramakrishna Vedantam Devi Parikh Dhruv Batra FAtt 325 20,110 0 07 Oct 2016
Top-down Neural Attention by Excitation Backprop Jianming Zhang Zhe Lin Jonathan Brandt Xiaohui Shen Stan Sclaroff 92 948 0 01 Aug 2016
The Latin American Giant Observatory: a successful collaboration in Latin America based on Cosmic Rays and computer science domains Hernán Asorey R. Mayo-García L. Núñez M. Pascual A. J. Rubio-Montero M. Suárez-Durán L. A. Torres-Niño 91 5 0 30 May 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 17,033 0 16 Feb 2016
Learning Deep Features for Discriminative Localization Bolei Zhou A. Khosla Àgata Lapedriza A. Oliva Antonio Torralba SSL SSeg FAtt 253 9,338 0 14 Dec 2015
Visualizing Deep Convolutional Neural Networks Using Natural Pre-Images Aravindh Mahendran Andrea Vedaldi FAtt 74 536 0 07 Dec 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 367 19,733 0 09 Mar 2015
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 254 4,681 0 21 Dec 2014
Understanding Deep Image Representations by Inverting Them Aravindh Mahendran Andrea Vedaldi FAtt 131 1,967 0 26 Nov 2014
Going Deeper with Convolutions Christian Szegedy Wei Liu Yangqing Jia P. Sermanet Scott E. Reed Dragomir Anguelov D. Erhan Vincent Vanhoucke Andrew Rabinovich 494 43,698 0 17 Sep 2014
Microsoft COCO: Common Objects in Context Nayeon Lee Michael Maire Serge J. Belongie Lubomir Bourdev Ross B. Girshick James Hays Pietro Perona Deva Ramanan C. L. Zitnick Piotr Dollár ObjD 434 43,832 0 01 May 2014
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 314 7,317 0 20 Dec 2013
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 595 15,904 0 12 Nov 2013