Generating Visual Explanations

28 March 2016

Bernt Schiele

Papers citing "Generating Visual Explanations"

50 / 125 papers shown

Title
A Review on Explainability in Multimodal Deep Neural Nets Gargi Joshi Rahee Walambe K. Kotecha 29 140 0 17 May 2021
A Comprehensive Taxonomy for Explainable Artificial Intelligence: A Systematic Survey of Surveys on Methods and Concepts Gesina Schwalbe Bettina Finzel XAI 29 184 0 15 May 2021
e-ViL: A Dataset and Benchmark for Natural Language Explanations in Vision-Language Tasks Maxime Kayser Oana-Maria Camburu Leonard Salewski Cornelius Emde Virginie Do Zeynep Akata Thomas Lukasiewicz VLM 26 100 0 08 May 2021
A First Look: Towards Explainable TextVQA Models via Visual and Textual Explanations Varun Nagaraj Rao Xingjian Zhen K. Hovsepian Mingwei Shen 37 18 0 29 Apr 2021
Revisiting The Evaluation of Class Activation Mapping for Explainability: A Novel Metric and Experimental Analysis Samuele Poppi Marcella Cornia Lorenzo Baraldi Rita Cucchiara FAtt 131 33 0 20 Apr 2021
Diagnosing Vision-and-Language Navigation: What Really Matters Wanrong Zhu Yuankai Qi P. Narayana Kazoo Sone Sugato Basu Qing Guo Qi Wu Miguel P. Eckstein Wei Wang LM&Ro 27 50 0 30 Mar 2021
Local Interpretations for Explainable Natural Language Processing: A Survey Siwen Luo Hamish Ivison S. Han Josiah Poon MILM 40 48 0 20 Mar 2021
KANDINSKYPatterns -- An experimental exploration environment for Pattern Analysis and Machine Intelligence Andreas Holzinger Anna Saranti Heimo Mueller 46 10 0 28 Feb 2021
Explainability of deep vision-based autonomous driving systems: Review and challenges Éloi Zablocki H. Ben-younes P. Pérez Matthieu Cord XAI 48 170 0 13 Jan 2021
Explaining Deep Neural Networks Oana-Maria Camburu XAI FAtt 33 26 0 04 Oct 2020
Where is the Model Looking At?--Concentrate and Explain the Network Attention Wenjia Xu Jiuniu Wang Yang Wang Guangluan Xu Wei Dai Yirong Wu XAI 29 17 0 29 Sep 2020
Contextual Semantic Interpretability Diego Marcos Ruth C. Fong Sylvain Lobry Rémi Flamary Nicolas Courty D. Tuia SSL 20 27 0 18 Sep 2020
Contrastive Explanations in Neural Networks Mohit Prabhushankar Gukyeong Kwon Dogancan Temel Ghassan AlRegib FAtt 8 33 0 01 Aug 2020
The Impact of Explanations on AI Competency Prediction in VQA Kamran Alipour Arijit Ray Xiaoyu Lin J. Schulze Yi Yao Giedrius Burachas 27 9 0 02 Jul 2020
Drug discovery with explainable artificial intelligence José Jiménez-Luna F. Grisoni G. Schneider 30 626 0 01 Jul 2020
A generalizable saliency map-based interpretation of model outcome Shailja Thakur S. Fischmeister AAML FAtt MILM 24 2 0 16 Jun 2020
AI Research Considerations for Human Existential Safety (ARCHES) Andrew Critch David M. Krueger 30 50 0 30 May 2020
Don't Explain without Verifying Veracity: An Evaluation of Explainable AI with Video Activity Recognition Mahsan Nourani Chiradeep Roy Tahrima Rahman Eric D. Ragan Nicholas Ruozzi Vibhav Gogate AAML 15 17 0 05 May 2020
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 41 371 0 30 Apr 2020
Adversarial Robustness on In- and Out-Distribution Improves Explainability Maximilian Augustin Alexander Meinke Matthias Hein OOD 75 99 0 20 Mar 2020
A Study on Multimodal and Interactive Explanations for Visual Question Answering Kamran Alipour J. Schulze Yi Yao Avi Ziskind Giedrius Burachas 32 27 0 01 Mar 2020
Learning Global Transparent Models Consistent with Local Contrastive Explanations Tejaswini Pedapati Avinash Balakrishnan Karthikeyan Shanmugam Amit Dhurandhar FAtt 22 0 0 19 Feb 2020
Evaluating Saliency Map Explanations for Convolutional Neural Networks: A User Study Ahmed Alqaraawi M. Schuessler Philipp Weiß Enrico Costanza N. Bianchi-Berthouze AAML FAtt XAI 33 197 0 03 Feb 2020
CheXplain: Enabling Physicians to Explore and UnderstandData-Driven, AI-Enabled Medical Imaging Analysis Yao Xie Melody Chen David Kao Ge Gao Xiang Ánthony' Chen 31 126 0 15 Jan 2020
Keeping Community in the Loop: Understanding Wikipedia Stakeholder Values for Machine Learning-Based Systems C. E. Smith Bowen Yu Anjali Srivastava Aaron L Halfaker Loren G. Terveen Haiyi Zhu KELM 21 69 0 14 Jan 2020
On the Explanation of Machine Learning Predictions in Clinical Gait Analysis D. Slijepcevic Fabian Horst Sebastian Lapuschkin Anna-Maria Raberger Matthias Zeppelzauer Wojciech Samek C. Breiteneder W. Schöllhorn B. Horsak 36 50 0 16 Dec 2019
TAB-VCR: Tags and Attributes based Visual Commonsense Reasoning Baselines Jingxiang Lin Unnat Jain A. Schwing LRM ReLM 34 9 0 31 Oct 2019
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 39 6,119 0 22 Oct 2019
Semantically Interpretable Activation Maps: what-where-how explanations within CNNs Diego Marcos Sylvain Lobry D. Tuia FAtt MILM 22 26 0 18 Sep 2019
Class Feature Pyramids for Video Explanation Alexandros Stergiou G. Kapidis Grigorios Kalliatakis C. Chrysoulas R. Poppe R. Veltkamp FAtt 33 18 0 18 Sep 2019
X-ToM: Explaining with Theory-of-Mind for Gaining Justified Human Trust Arjun Reddy Akula Changsong Liu Sari Saba-Sadiya Hongjing Lu S. Todorovic J. Chai Song-Chun Zhu 24 18 0 15 Sep 2019
Neural Naturalist: Generating Fine-Grained Image Comparisons Maxwell Forbes Christine Kaeser-Chen Piyush Sharma Serge J. Belongie VLM 64 56 0 09 Sep 2019
Grid Saliency for Context Explanations of Semantic Segmentation Lukas Hoyer Mauricio Muñoz P. Katiyar Anna Khoreva Volker Fischer FAtt 25 48 0 30 Jul 2019
On the Weaknesses of Reinforcement Learning for Neural Machine Translation Leshem Choshen Lior Fox Zohar Aizenbud Omri Abend 17 104 0 03 Jul 2019
Explainability in Human-Agent Systems A. Rosenfeld A. Richardson XAI 27 203 0 17 Apr 2019
f-VAEGAN-D2: A Feature Generating Framework for Any-Shot Learning Yongqin Xian Saurabh Sharma Bernt Schiele Zeynep Akata GAN VLM 36 483 0 25 Mar 2019
Generating Natural Language Explanations for Visual Question Answering using Scene Graphs and Visual Attention Shalini Ghosh Giedrius Burachas Arijit Ray Avi Ziskind 19 65 0 15 Feb 2019
Interactive Naming for Explaining Deep Neural Networks: A Formative Study M. Hamidi-Haines Zhongang Qi Alan Fern Fuxin Li Prasad Tadepalli FAtt HAI 14 11 0 18 Dec 2018
Learning to Explain with Complemental Examples Atsushi Kanehira Tatsuya Harada 12 40 0 04 Dec 2018
Multimodal Explanations by Predicting Counterfactuality in Videos Atsushi Kanehira Kentaro Takemoto S. Inayoshi Tatsuya Harada 26 35 0 04 Dec 2018
From Recognition to Cognition: Visual Commonsense Reasoning Rowan Zellers Yonatan Bisk Ali Farhadi Yejin Choi LRM BDL OCL ReLM 58 867 0 27 Nov 2018
Semantic bottleneck for computer vision tasks Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard 16 15 0 06 Nov 2018
Understanding the Origins of Bias in Word Embeddings Marc-Etienne Brunet Colleen Alkalay-Houlihan Ashton Anderson R. Zemel FaML 26 198 0 08 Oct 2018
Faithful Multimodal Explanation for Visual Question Answering Jialin Wu Raymond J. Mooney 20 90 0 08 Sep 2018
Using Machine Learning Safely in Automotive Software: An Assessment and Adaption of Software Process Requirements in ISO 26262 Rick Salay Krzysztof Czarnecki 25 69 0 05 Aug 2018
Grounding Visual Explanations Lisa Anne Hendricks Ronghang Hu Trevor Darrell Zeynep Akata FAtt 17 225 0 25 Jul 2018
Generating Counterfactual Explanations with Natural Language Lisa Anne Hendricks Ronghang Hu Trevor Darrell Zeynep Akata FAtt 15 99 0 26 Jun 2018
Interpretable to Whom? A Role-based Model for Analyzing Interpretable Machine Learning Systems Richard J. Tomsett Dave Braines Daniel Harborne Alun D. Preece Supriyo Chakraborty FaML 29 164 0 20 Jun 2018
Contrastive Explanations with Local Foil Trees J. V. D. Waa M. Robeer J. Diggelen Matthieu J. S. Brinkhuis Mark Antonius Neerincx FAtt 19 82 0 19 Jun 2018
RISE: Randomized Input Sampling for Explanation of Black-box Models Vitali Petsiuk Abir Das Kate Saenko FAtt 67 1,151 0 19 Jun 2018