Opti-CAM: Optimizing saliency maps for interpretability

Opti-CAM: Optimizing saliency maps for interpretability

17 January 2023

Yannis Avrithis

Stéphane Ayache

Papers citing "Opti-CAM: Optimizing saliency maps for interpretability"

19 / 19 papers shown

Title
DocVXQA: Context-Aware Visual Explanations for Document Question Answering Mohamed Ali Souibgui Changkyu Choi Andrey Barsky Kangsoo Jung Ernest Valveny Dimosthenis Karatzas 18 0 0 12 May 2025
Generating visual explanations from deep networks using implicit neural representations Michal Byra Henrik Skibbe GAN FAtt 29 0 0 20 Jan 2025
CNN Explainability with Multivector Tucker Saliency Maps for Self-Supervised Models Aymene Mohammed Bouayed Samuel Deslauriers-Gauthier Adrian Iaccovelli D. Naccache 23 0 0 30 Oct 2024
The Overfocusing Bias of Convolutional Neural Networks: A Saliency-Guided Regularization Approach David Bertoin Eduardo Hugo Sanchez Mehdi Zouitine Emmanuel Rachelson 23 0 0 25 Sep 2024
PEPL: Precision-Enhanced Pseudo-Labeling for Fine-Grained Image Classification in Semi-Supervised Learning Bowen Tian Songning Lai Lujundong Li Zhihao Shuai Runwei Guan Tian Wu Yutao Yue VLM 21 0 0 05 Sep 2024
Listenable Maps for Zero-Shot Audio Classifiers Francesco Paissan Luca Della Libera Mirco Ravanelli Cem Subakan 32 4 0 27 May 2024
A Learning Paradigm for Interpretable Gradients Felipe Figueroa Hanwei Zhang R. Sicre Yannis Avrithis Stéphane Ayache FAtt 13 0 0 23 Apr 2024
CA-Stream: Attention-based pooling for interpretable image recognition Felipe Torres Hanwei Zhang R. Sicre Stéphane Ayache Yannis Avrithis 44 0 0 23 Apr 2024
CAM-Based Methods Can See through Walls Magamed Taimeskhanov R. Sicre Damien Garreau 14 1 0 02 Apr 2024
On the stability, correctness and plausibility of visual explanation methods based on feature importance Romain Xu-Darme Jenny Benois-Pineau R. Giot Georges Quénot Zakaria Chihani M. Rousset Alexey Zhukov XAI FAtt 12 1 0 25 Oct 2023
Explanation-based Training with Differentiable Insertion/Deletion Metric-aware Regularizers Yuya Yoshikawa Tomoharu Iwata 14 0 0 19 Oct 2023
SPADE: Sparsity-Guided Debugging for Deep Neural Networks Arshia Soltani Moakhar Eugenia Iofinova Elias Frantar Dan Alistarh 32 1 0 06 Oct 2023
UPDExplainer: an Interpretable Transformer-based Framework for Urban Physical Disorder Detection Using Street View Imagery Chuanbo Hu Shan Jia Fan Zhang C. Xiao Mindi Ruan Jacob Thrasher Xin Li 18 10 0 04 May 2023
Metrics for saliency map evaluation of deep learning explanation methods T. Gomez Thomas Fréour Harold Mouchère XAI FAtt 64 41 0 31 Jan 2022
Revisiting The Evaluation of Class Activation Mapping for Explainability: A Novel Metric and Experimental Analysis Samuele Poppi Marcella Cornia Lorenzo Baraldi Rita Cucchiara FAtt 125 33 0 20 Apr 2021
Benchmarking and Survey of Explanation Methods for Black Box Models F. Bodria F. Giannotti Riccardo Guidotti Francesca Naretto D. Pedreschi S. Rinzivillo XAI 33 218 0 25 Feb 2021
Investigating and Simplifying Masking-based Saliency Methods for Model Interpretability Jason Phang Jungkyu Park Krzysztof J. Geras FAtt AAML 209 7 0 19 Oct 2020
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,233 0 24 Jun 2017
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 282 39,170 0 01 Sep 2014