saliency map

CAMERAS: Enhanced Resolution and Sanity Preserving Class Activation Mapping for Image Saliency CVPR 2021 CheXseg: Combining Expert Annotations with DNN-generated Saliency Maps for X-ray Segmentation MIDL 2021 DANCE: Enhancing saliency maps using decoys ICML 2021 Do Different Deep Metric Learning Losses Lead to Similar Learned Features? ICCV 2021 Explainable Image Quality Analysis of Chest X-Rays MIDL 2021 Explainable Models with Consistent Interpretations AAAI 2021 GANMEX: One-vs-One Attributions using GAN-based Model Explainability ICML 2021 Generating Deep Networks Explanations with Robust Attribution Alignment ACML 2021 Guided Integrated Gradients: An Adaptive Path Method for Removing Noise CVPR 2021 Identifying untrustworthy predictions in neural networks by geometric gradient analysis UAI 2021 KeepAugment: A Simple Information-Preserving Data Augmentation Approach CVPR 2021 Machine versus Human Attention in Deep Reinforcement Learning Tasks NeurIPS 2021 Relevance-CAM: Your Model Already Knows Where To Look CVPR 2021 Saliency-Guided Image Translation CVPR 2021 Saliency is a Possible Red Herring When Diagnosing Poor Generalization ICLR 2021 SaliencyMix: A Saliency Guided Data Augmentation Strategy for Better Regularization ICLR 2021 Scaling Symbolic Methods using Gradients for Neural Model Explanation ICLR 2021 SWAG: Superpixels Weighted by Average Gradients for Explanations of CNNs WACV 2021 Weakly-supervised High-resolution Segmentation of Mammography Images for Breast Cancer Diagnosis MIDL 2021 AtLoc: Attention Guided Camera Localization AAAI 2020 Attribution in Scale and Space CVPR 2020 Explaining Black Box Predictions and Unveiling Data Artifacts through Influence Functions ACL 2020 Explain Your Move: Understanding Agent Actions Using Specific and Relevant Feature Attribution ICLR 2020 Explanation by Progressive Exaggeration ICLR 2020 Exploratory Not Explanatory: Counterfactual Analysis of Saliency Maps for Deep Reinforcement Learning ICLR 2020