Adaptive occlusion sensitivity analysis for visually explaining video recognition networks

26 July 2022

Papers citing "Adaptive occlusion sensitivity analysis for visually explaining video recognition networks"

38 / 38 papers shown

Title
Is Appearance Free Action Recognition Possible? Filip Ilic Thomas Pock Richard P. Wildes 39 15 0 13 Jul 2022
Intriguing Properties of Vision Transformers Muzammal Naseer Kanchana Ranasinghe Salman Khan Munawar Hayat Fahad Shahbaz Khan Ming-Hsuan Yang ViT 304 641 0 21 May 2021
Group-CAM: Group Score-Weighted Visual Explanations for Deep Convolutional Networks Qing-Long Zhang Lu Rao Yubin Yang 34 58 0 25 Mar 2021
Is Space-Time Attention All You Need for Video Understanding? Gedas Bertasius Heng Wang Lorenzo Torresani ViT 362 2,039 0 09 Feb 2021
A Survey on Neural Network Interpretability Yu Zhang Peter Tiño A. Leonardis K. Tang FaML XAI 192 676 0 28 Dec 2020
Quantifying Attention Flow in Transformers Samira Abnar Willem H. Zuidema 132 794 0 02 May 2020
Would Mega-scale Datasets Further Enhance Spatiotemporal 3D CNNs? Hirokatsu Kataoka Tenga Wakamiya Kensho Hara Y. Satoh 3DPC 119 89 0 10 Apr 2020
There and Back Again: Revisiting Backpropagation Saliency Methods Sylvestre-Alvise Rebuffi Ruth C. Fong Xu Ji Andrea Vedaldi FAtt XAI 66 113 0 06 Apr 2020
Explaining Motion Relevance for Activity Recognition in Video Deep Learning Models Liam Hiley Alun D. Preece Y. Hicks Supriyo Chakraborty Prudhvi K. Gurram Richard J. Tomsett FAtt 57 15 0 31 Mar 2020
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI Alejandro Barredo Arrieta Natalia Díaz Rodríguez Javier Del Ser Adrien Bennetot Siham Tabik ... S. Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila Francisco Herrera XAI 116 6,251 0 22 Oct 2019
Understanding Deep Networks via Extremal Perturbations and Smooth Masks Ruth C. Fong Mandela Patrick Andrea Vedaldi AAML 64 415 0 18 Oct 2019
A Survey on Explainable Artificial Intelligence (XAI): Towards Medical XAI Erico Tjoa Cuntai Guan XAI 89 1,444 0 17 Jul 2019
A Short Note on the Kinetics-700 Human Action Dataset João Carreira Eric Noland Chloe Hillier Andrew Zisserman 70 450 0 15 Jul 2019
Saliency Tubes: Visual Explanations for Spatio-Temporal Convolutions Alexandros Stergiou G. Kapidis Grigorios Kalliatakis C. Chrysoulas R. Veltkamp R. Poppe FAtt 49 47 0 04 Feb 2019
SlowFast Networks for Video Recognition Christoph Feichtenhofer Haoqi Fan Jitendra Malik Kaiming He 162 3,262 0 10 Dec 2018
Sanity Checks for Saliency Maps Julius Adebayo Justin Gilmer M. Muelly Ian Goodfellow Moritz Hardt Been Kim FAtt AAML XAI 123 1,963 0 08 Oct 2018
RISE: Randomized Input Sampling for Explanation of Black-box Models Vitali Petsiuk Abir Das Kate Saenko FAtt 172 1,169 0 19 Jun 2018
A Closer Look at Spatiotemporal Convolutions for Action Recognition Du Tran Heng Wang Lorenzo Torresani Jamie Ray Yann LeCun Manohar Paluri 196 3,021 0 30 Nov 2017
Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks Aditya Chattopadhyay Anirban Sarkar Prantik Howlader V. Balasubramanian FAtt 101 2,289 0 30 Oct 2017
Learning Spatio-Temporal Features with 3D Residual Networks for Action Recognition Kensho Hara Hirokatsu Kataoka Y. Satoh 3DPC 74 604 0 25 Aug 2017
SmoothGrad: removing noise by adding noise D. Smilkov Nikhil Thorat Been Kim F. Viégas Martin Wattenberg FAtt ODL 199 2,221 0 12 Jun 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.0K 21,815 0 22 May 2017
The Kinetics Human Action Video Dataset W. Kay João Carreira Karen Simonyan Brian Zhang Chloe Hillier ... Tim Green T. Back Apostol Natsev Mustafa Suleyman Andrew Zisserman 228 3,796 0 19 May 2017
Interpretable Explanations of Black Boxes by Meaningful Perturbation Ruth C. Fong Andrea Vedaldi FAtt AAML 74 1,517 0 11 Apr 2017
Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Kundaje FAtt 186 3,865 0 10 Apr 2017
Understanding Black-box Predictions via Influence Functions Pang Wei Koh Percy Liang TDI 169 2,878 0 14 Mar 2017
Visualizing Deep Neural Network Decisions: Prediction Difference Analysis L. Zintgraf Taco S. Cohen T. Adel Max Welling FAtt 132 707 0 15 Feb 2017
Learning Features by Watching Objects Move Deepak Pathak Ross B. Girshick Piotr Dollár Trevor Darrell Bharath Hariharan SSL VOS OCL 67 525 0 19 Dec 2016
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 266 19,929 0 07 Oct 2016
Top-down Neural Attention by Excitation Backprop Jianming Zhang Zhe Lin Jonathan Brandt Xiaohui Shen Stan Sclaroff 79 947 0 01 Aug 2016
Not Just a Black Box: Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Shcherbina A. Kundaje FAtt 80 786 0 05 May 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.1K 16,931 0 16 Feb 2016
Learning Deep Features for Discriminative Localization Bolei Zhou A. Khosla Àgata Lapedriza A. Oliva Antonio Torralba SSL SSeg FAtt 239 9,305 0 14 Dec 2015
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 238 4,665 0 21 Dec 2014
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 299 7,289 0 20 Dec 2013
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 552 15,874 0 12 Nov 2013
UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild K. Soomro Amir Zamir M. Shah CLIP VGen 135 6,145 0 03 Dec 2012
How to Explain Individual Classification Decisions D. Baehrens T. Schroeter Stefan Harmeling M. Kawanabe K. Hansen K. Müller FAtt 126 1,102 0 06 Dec 2009