Conference article  Open Access

AIMH Lab 2022 activities for Vision

Ciampi L., Amato G., Bolettieri P., Carrara F., Di Benedetto M., Falchi F., Gennaro C., Messina N., Vadicamo L., Vairo C.

Computer vision  Deep Learning  Large-scale video retrieval  Learning with scarce data  Multimedia understanding 

The explosion of smartphones and cameras has led to a vast production of multimedia data. Consequently, Artificial Intelligence-based tools for automatically understanding and exploring these data have recently gained much attention. In this short paper, we report some activities of the Artificial Intelligence for Media and Humanities (AIMH) laboratory of the ISTI-CNR, tackling some challenges in the field of Computer Vision for the automatic understanding of visual data and for novel interactive tools aimed at multimedia data exploration. Specifically, we provide innovative solutions based on Deep Learning techniques carrying out typical vision tasks such as object detection and visual counting, with particular emphasis on scenarios characterized by scarcity of labeled data needed for the supervised training and on environments with limited power resources imposing miniaturization of the models. Furthermore, we describe VISIONE, our large-scale video search system designed to search extensive multimedia databases in an interactive and user-friendly manner.

Source: Ital-IA 2023, pp. 538–543, Pisa, Italy, 29-31/05/2023

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BibTeX entry
	title = {AIMH Lab 2022 activities for Vision},
	author = {Ciampi L. and Amato G. and Bolettieri P. and Carrara F. and Di Benedetto M. and Falchi F. and Gennaro C. and Messina N. and Vadicamo L. and Vairo C.},
	booktitle = {Ital-IA 2023, pp. 538–543, Pisa, Italy, 29-31/05/2023},
	year = {2023}

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