Zero-Shot Age Estimation for Child Sexual Abuse Material

• Grant number: 24/09375-1
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: August 01, 2024
• Status: Discontinued
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: Sandra Eliza Fontes de Avila
• Grantee: Caio Petrucci dos Santos Rosa
• Host Institution: Instituto de Computação (IC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated research grant: 23/12086-9 - Araceli: Artificial Intelligence in the Fight Against Child Sexual Abuse, AP.R

Abstract

Child sexual abuse materials (CSAM) have reached alarming proportions in the digital age. According to the National Center for Missing and Exploited Children's CyberTipline, over 36 million reports of suspected CSAM were received in 2023, making it a record year. The availability and sharing of such harmful content online not only exacerbate the trauma inflicted upon the victims but also significantly burden law-enforcement agents who have to inspect thousands of files, leading to emotional strain manually. In light of that, there is a need for reliable automated tools that can handle this kind of material securely and efficiently. We aim in this project at the highly related task of zero-shot age estimation, which combines one of the core aspects of CSAM recognition - estimating the age of people within an image - with a restriction on the data used for training; we make our age estimation task zero-shot by not making use of any images of children within our training pipeline, a constraint inspired and aligned with the UNICEF's Responsible Data for Children Report which asks for either principled handling of data linked to children or to avoid its use for training models in the first place.

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

CAETANO, CARLOS; FERRAZ RIBEIRO, LEO SAMPAIO; LARANJEIRA, CAMILA; DOS SANTOS, GABRIEL OLIVEIRA; BARROS, ARTUR; PETRUCCI, CAIO; DOS SANTOS, ANDREZA APARECIDA; MACEDO, JOAO; CARVALHO, GIL; BENEVENUTO, FABRICIO; et al. Mastering Scene Understanding: Scene Graphs to the Rescue. 2024 37TH SIBGRAPI CONFERENCE ON GRAPHICS, PATTERNS AND IMAGES, SIBGRAPI 2024, v. N/A, p. 6-pg., 2024-01-01. (24/01210-3, 24/09372-2, 20/09838-0, 22/14690-8, 24/09375-1, 13/08293-7, 23/12086-9)