3 citations · 8 across the 8 of their papers we have counts for
6 papers · 1 filter
A Unified Non-Parametric and Interpretable Point Cloud Analysis via t-FCW Graph Representation
Haijian Lai, Bowen Liu, Man Xu +4
We introduce an empowered transposed Fully Connected Weighted (t-FCW) graph representation to embed point clouds into a metric space. While original t-FCW has shown promising resul…
CSA-Graphs: A Privacy-Preserving Structural Dataset for Child Sexual Abuse Research
Carlos Caetano, Camila Laranjeira, Clara Ernesto +5
Child Sexual Abuse Imagery (CSAI) classification is an important yet challenging problem for computer vision research due to the strict legal and ethical restrictions that prevent…
Human-Centric Perception for Child Sexual Abuse Imagery
Camila Laranjeira, João Macedo, Sandra Avila +2
Law enforcement agencies and non-gonvernmental organizations handling reports of Child Sexual Abuse Imagery (CSAI) are overwhelmed by large volumes of data, requiring the aid of au…
Attention over Scene Graphs: Indoor Scene Representations Toward CSAI Classification
Artur Barros, Carlos Caetano, João Macedo +2
Indoor scene classification is a critical task in computer vision, with wide-ranging applications that go from robotics to sensitive content analysis, such as child sexual abuse im…
Leveraging Self-Supervised Learning for Scene Classification in Child Sexual Abuse Imagery
Pedro H. V. Valois, João Macedo, Leo S. F. Ribeiro +2
Crime in the 21st century is split into a virtual and real world. However, the former has become a global menace to people's well-being and security in the latter. The challenges i…
Seeing without Looking: Analysis Pipeline for Child Sexual Abuse Datasets
Camila Laranjeira, João Macedo, Sandra Avila +1
The online sharing and viewing of Child Sexual Abuse Material (CSAM) are growing fast, such that human experts can no longer handle the manual inspection. However, the automatic cl…