Explainable AI
Visualizing Deep Networks by Optimizing with Integrated Gradients-
[pdf]
[bibtex]@InProceedings{Qi_2019_CVPR_Workshops,
author = {Qi, Zhongang and Khorram, Saeed and Li, Fuxin},
title = {Visualizing Deep Networks by Optimizing with Integrated Gradients},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Deep Coupling of Random Ferns-
[pdf]
[bibtex]@InProceedings{Kim_2019_CVPR_Workshops,
author = {Kim, Sangwon and Jeong, Mira and Lee, Deokwoo and Chul Ko, Byoung},
title = {Deep Coupling of Random Ferns},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Unsupervised clustering based understanding of CNN-
[pdf]
[bibtex]@InProceedings{Girish_2019_CVPR_Workshops,
author = {Girish, Deeptha and Singh, Vineeta and Ralescu, Anca},
title = {Unsupervised clustering based understanding of CNN},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Identifying Interpretable Action Concepts in Deep Networks-
[pdf]
[bibtex]@InProceedings{Ramakrishnan_2019_CVPR_Workshops,
author = {Ramakrishnan, Kandan and Monfort, Mathew and A McNamara, Barry and Lascelles, Alex and Gutfreund, Dan and Feris, Rogerio and Oliva, Aude},
title = {Identifying Interpretable Action Concepts in Deep Networks},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Beyond Explainability: Leveraging Interpretability for Improved Adversarial Learning-
[pdf]
[bibtex]@InProceedings{Daya_2019_CVPR_Workshops,
author = {Kumarl Ibrahim Ben Daya, Devinder and Vats, Kanav and Feng, Jeffery and Taylor, Graham and Wong, Alexander},
title = {Beyond Explainability: Leveraging Interpretability for Improved Adversarial Learning},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Building Explainable AI Evaluation for Autonomous Perception-
[pdf]
[bibtex]@InProceedings{Zhang_2019_CVPR_Workshops,
author = {Zhang, Chi and Shang, Biyao and Wei, Ping and Li, Li and Liu, Yuehu and Zheng, Nanning},
title = {Building Explainable AI Evaluation for Autonomous Perception},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Unit Impulse Response as an Explainer of Redundancy in a Deep Convolutional Neural Network-
[pdf]
[bibtex]@InProceedings{Sathish_2019_CVPR_Workshops,
author = {Sathish, Rachana and Sheet, Debdoot},
title = {Unit Impulse Response as an Explainer of Redundancy in a Deep Convolutional Neural Network},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Localizing Common Objects Using Common Component Activation Map-
[pdf]
[bibtex]@InProceedings{Li_2019_CVPR_Workshops,
author = {Li, Weihao and Hosseini Jafari, Omid and Rother, Carsten},
title = {Localizing Common Objects Using Common Component Activation Map},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Interpretation of Deep CNN Recognition with Filter Space Clustering in Feature Extraction and Reconstruction-
[pdf]
[bibtex]@InProceedings{Lee_2019_CVPR_Workshops,
author = {Lee, Sukhan and Ul Islam, Naeem},
title = {Interpretation of Deep CNN Recognition with Filter Space Clustering in Feature Extraction and Reconstruction},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Interpretation of Feature Space using Multi-Channel Attentional Sub-Networks-
[pdf]
[bibtex]@InProceedings{Kimura_2019_CVPR_Workshops,
author = {Kimura, Masanari and Tanaka, Masayuki},
title = {Interpretation of Feature Space using Multi-Channel Attentional Sub-Networks},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Relevance Regularization of Convolutional Neural Network for Interpretable Classification-
[pdf]
[bibtex]@InProceedings{Yoo_2019_CVPR_Workshops,
author = {Hwa Yoo, Chae and Kim, Nayoung and Kang, Je-Won},
title = {Relevance Regularization of Convolutional Neural Network for Interpretable Classification},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Interpretable Machine Learning for Generating Semantically Meaningful Formative Feedback-
[pdf]
[bibtex]@InProceedings{Alyuz_2019_CVPR_Workshops,
author = {Alyuz, Nese and Metin Sezgin, Tevfik},
title = {Interpretable Machine Learning for Generating Semantically Meaningful Formative Feedback},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
To believe or not to believe: Validating explanation fidelity for dynamic malware analysis-
[pdf]
[bibtex]@InProceedings{Chen_2019_CVPR_Workshops,
author = {Chen, Li and Yagemann, Carter and Downing, Evan},
title = {To believe or not to believe: Validating explanation fidelity for dynamic malware analysis},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Learning Semantically Meaningful Embeddings Using Linear Constraints-
[pdf]
[bibtex]@InProceedings{Lin_2019_CVPR_Workshops,
author = {Lin, Shuyu and Yang, Bo and Birke, Robert and Clark, Ronald},
title = {Learning Semantically Meaningful Embeddings Using Linear Constraints},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Deep Visual City Recognition Visualization-
[pdf]
[bibtex]@InProceedings{Shi_2019_CVPR_Workshops,
author = {Shi, Xiangwei and Khademi, Seyran and van Gemert, Jan},
title = {Deep Visual City Recognition Visualization},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Explainable Hierarchical Semantic Convolutional Neural Network for Lung Cancer Diagnosis-
[pdf]
[bibtex]@InProceedings{Shen_2019_CVPR_Workshops,
author = {Shen, Shiwen and X Han, Simon and R Aberle, Denise and A Bui, Alex and Hsu, William},
title = {Explainable Hierarchical Semantic Convolutional Neural Network for Lung Cancer Diagnosis},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Are CNN Predictions based on Reasonable Evidence?-
[pdf]
[bibtex]@InProceedings{Bargal_2019_CVPR_Workshops,
author = {Adel Bargal, Sarah and Zunino, Andrea and Petsiuk, Vitali and Zhang, Jianming and Saenko, Kate and Murino, Vittorio and Sclaroff, Stan},
title = {Are CNN Predictions based on Reasonable Evidence?},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Explaining the PointNet: What Has Been Learned Inside the PointNet?-
[pdf]
[bibtex]@InProceedings{Zhang_2019_CVPR_Workshops,
author = {Zhang, Binbin and Huang, Shikun and Shen, Wen and Wei, Zhihua},
title = {Explaining the PointNet: What Has Been Learned Inside the PointNet?},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Towards an Understanding of Neural Networks in Natural-Image Spaces-
[pdf]
[bibtex]@InProceedings{Fan_2019_CVPR_Workshops,
author = {Fan, Yifei and Yezzi, Anthony},
title = {Towards an Understanding of Neural Networks in Natural-Image Spaces},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Geometric interpretation of a CNN's last layer-
[pdf]
[bibtex]@InProceedings{Calle_2019_CVPR_Workshops,
author = {de la Calle, Alejandro and Aller, Aitor and Tovar, Javier and Almazan, Emilio J.},
title = {Geometric interpretation of a CNN's last layer},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Medical Time Series Classification with Hierarchical Attention-based Temporal Convolutional Networks: A Case Study of Myotonic Dystrophy Diagnosis-
[pdf]
[bibtex]@InProceedings{Lin_2019_CVPR_Workshops,
author = {Lin, Lei and Xu, Beilei and Wu, Wencheng and Richardson, Trevor W. and Bernal, Edgar A.},
title = {Medical Time Series Classification with Hierarchical Attention-based Temporal Convolutional Networks: A Case Study of Myotonic Dystrophy Diagnosis},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Natural Language Interaction with Explainable AI Models-
[pdf]
[bibtex]@InProceedings{Akula_2019_CVPR_Workshops,
author = {R Akula, Arjun and Todorovic, Sinisa and Y Chai, Joyce and Zhu, Song-Chun},
title = {Natural Language Interaction with Explainable AI Models},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Explainable AI as Collaborative Task Solving-
[pdf]
[bibtex]@InProceedings{Akula_2019_CVPR_Workshops,
author = {Akula, Arjun and Liu, Changsong and Todorovic, Sinisa and Chai, Joyce and Zhu, Song-Chun},
title = {Explainable AI as Collaborative Task Solving},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Explainability for Content-Based Image Retrieval-
[pdf]
[bibtex]@InProceedings{Dong_2019_CVPR_Workshops,
author = {Dong, Bo and Collins, Roddy and Hoogs, Anthony},
title = {Explainability for Content-Based Image Retrieval},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Analysis of the contribution and temporal dependency of LSTM layers for reinforcement learning tasks-
[pdf]
[bibtex]@InProceedings{Lee_2019_CVPR_Workshops,
author = {Lee, Teng-Yok and van Baar, Jeroen and Wittenburg, Kent and Sullivan, Alan},
title = {Analysis of the contribution and temporal dependency of LSTM layers for reinforcement learning tasks},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Directing DNNs Attention for Facial Attribution Classification using Gradient-weighted Class Activation Mapping-
[pdf]
[bibtex]@InProceedings{Yang_2019_CVPR_Workshops,
author = {Yang, Xi and Wu, Bojian and Sato, Issei and Igarashi, Takeo},
title = {Directing DNNs Attention for Facial Attribution Classification using Gradient-weighted Class Activation Mapping},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Visualizing the Resilience of Deep Convolutional Network Interpretations-
[pdf]
[bibtex]@InProceedings{Vasu_2019_CVPR_Workshops,
author = {Vasu, Bhavan and Savakis, Andreas},
title = {Visualizing the Resilience of Deep Convolutional Network Interpretations},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Beauty Learning and Counterfactual Inference-
[pdf]
[bibtex]@InProceedings{Li_2019_CVPR_Workshops,
author = {Li, Tao},
title = {Beauty Learning and Counterfactual Inference},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
Visualizing the Decision-making Process in Deep Neural Decision Forest-
[pdf]
[bibtex]@InProceedings{Li_2019_CVPR_Workshops,
author = {Li, Shichao and Cheng, Kwang-Ting},
title = {Visualizing the Decision-making Process in Deep Neural Decision Forest},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
L1-Norm Gradient Penalty for Noise Reduction of Attribution Maps-
[pdf]
[bibtex]@InProceedings{Kiritoshi_2019_CVPR_Workshops,
author = {Kiritoshi, Keisuke and Tanno, Ryosuke and Izumitani, Tomonori},
title = {L1-Norm Gradient Penalty for Noise Reduction of Attribution Maps},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}