PrivLEX: Detecting legal concepts in images through Vision-Language Models

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Bibliographic Details
Main Authors:	Baranouskaya, Darya, Cavallaro, Andrea
Format:	Preprint
Published:	2026
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
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author	Baranouskaya, Darya Cavallaro, Andrea
author_facet	Baranouskaya, Darya Cavallaro, Andrea
contents	We present PrivLEX, a novel image privacy classifier that grounds its decisions in legally defined personal data concepts. PrivLEX is the first interpretable privacy classifier aligned with legal concepts that leverages the recognition capabilities of Vision-Language Models (VLMs). PrivLEX relies on zero-shot VLM concept detection to provide interpretable classification through a label-free Concept Bottleneck Model, without requiring explicit concept labels during training. We demonstrate PrivLEX's ability to identify personal data concepts that are present in images. We further analyse the sensitivity of such concepts as perceived by human annotators of image privacy datasets.
format	Preprint
id	arxiv_https___arxiv_org_abs_2601_09449
institution	arXiv
publishDate	2026
record_format	arxiv
spellingShingle	PrivLEX: Detecting legal concepts in images through Vision-Language Models Baranouskaya, Darya Cavallaro, Andrea Computer Vision and Pattern Recognition We present PrivLEX, a novel image privacy classifier that grounds its decisions in legally defined personal data concepts. PrivLEX is the first interpretable privacy classifier aligned with legal concepts that leverages the recognition capabilities of Vision-Language Models (VLMs). PrivLEX relies on zero-shot VLM concept detection to provide interpretable classification through a label-free Concept Bottleneck Model, without requiring explicit concept labels during training. We demonstrate PrivLEX's ability to identify personal data concepts that are present in images. We further analyse the sensitivity of such concepts as perceived by human annotators of image privacy datasets.
title	PrivLEX: Detecting legal concepts in images through Vision-Language Models
topic	Computer Vision and Pattern Recognition
url	https://arxiv.org/abs/2601.09449

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