Saved in:
Bibliographic Details
Main Authors: Yu, Hyeon, Benois-Pineau, Jenny, Bourqui, Romain, Giot, Romain, Zhukov, Alexey
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2407.20427
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866916339188236288
author Yu, Hyeon
Benois-Pineau, Jenny
Bourqui, Romain
Giot, Romain
Zhukov, Alexey
author_facet Yu, Hyeon
Benois-Pineau, Jenny
Bourqui, Romain
Giot, Romain
Zhukov, Alexey
contents This paper investigates the use of Mean Opinion Score (MOS), a common image quality metric, as a user-centric evaluation metric for XAI post-hoc explainers. To measure the MOS, a user experiment is proposed, which has been conducted with explanation maps of intentionally distorted images. Three methods from the family of feature attribution methods - Gradient-weighted Class Activation Mapping (Grad-CAM), Multi-Layered Feature Explanation Method (MLFEM), and Feature Explanation Method (FEM) - are compared with this metric. Additionally, the correlation of this new user-centric metric with automatic metrics is studied via Spearman's rank correlation coefficient. MOS of MLFEM shows the highest correlation with automatic metrics of Insertion Area Under Curve (IAUC) and Deletion Area Under Curve (DAUC). However, the overall correlations are limited, which highlights the lack of consensus between automatic and user-centric metrics.
format Preprint
id arxiv_https___arxiv_org_abs_2407_20427
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Mean Opinion Score as a New Metric for User-Evaluation of XAI Methods
Yu, Hyeon
Benois-Pineau, Jenny
Bourqui, Romain
Giot, Romain
Zhukov, Alexey
Computer Vision and Pattern Recognition
Image and Video Processing
I.4.7
This paper investigates the use of Mean Opinion Score (MOS), a common image quality metric, as a user-centric evaluation metric for XAI post-hoc explainers. To measure the MOS, a user experiment is proposed, which has been conducted with explanation maps of intentionally distorted images. Three methods from the family of feature attribution methods - Gradient-weighted Class Activation Mapping (Grad-CAM), Multi-Layered Feature Explanation Method (MLFEM), and Feature Explanation Method (FEM) - are compared with this metric. Additionally, the correlation of this new user-centric metric with automatic metrics is studied via Spearman's rank correlation coefficient. MOS of MLFEM shows the highest correlation with automatic metrics of Insertion Area Under Curve (IAUC) and Deletion Area Under Curve (DAUC). However, the overall correlations are limited, which highlights the lack of consensus between automatic and user-centric metrics.
title Mean Opinion Score as a New Metric for User-Evaluation of XAI Methods
topic Computer Vision and Pattern Recognition
Image and Video Processing
I.4.7
url https://arxiv.org/abs/2407.20427