P-TAME: Explain Any Image Classifier with Trained PerturbationsIEEE Open Journal of Signal Processing (JOSP), 2025 |
Towards Better Explanations for Object DetectionAsian Conference on Machine Learning (ACML), 2023 |
On The Coherence of Quantitative Evaluation of Visual ExplanationsComputer Vision and Image Understanding (CVIU), 2023 |
TAME: Attention Mechanism Based Feature Fusion for Generating
Explanation Maps of Convolutional Neural NetworksIEEE International Symposium on Multimedia (ISM), 2022 |
ViGAT: Bottom-up event recognition and explanation in video using
factorized graph attention networkIEEE Access (IEEE Access), 2022 |
Rethinking gradient weights' influence over saliency map estimationItalian National Conference on Sensors (INS), 2022 |