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cs.CV2024
Explaining an image classifier with a generative model conditioned by uncertainty
Adrien LeCoz, Stéphane Herbin, Faouzi Adjed
We propose to condition a generative model by a given image classifier uncertainty in order to analyze and explain its behavior. Preliminary experiments on synthetic data and a cor…
cs.CV2024
Leveraging generative models to characterize the failure conditions of image classifiers
Adrien LeCoz, Stéphane Herbin, Faouzi Adjed
We address in this work the question of identifying the failure conditions of a given image classifier. To do so, we exploit the capacity of producing controllable distributions of…
cs.CV2024
Efficient Exploration of Image Classifier Failures with Bayesian Optimization and Text-to-Image Models
Adrien LeCoz, Houssem Ouertatani, Stéphane Herbin +1
Image classifiers should be used with caution in the real world. Performance evaluated on a validation set may not reflect performance in the real world. In particular, classifiers…