Search Results for author: Stefano D'arrigo

Found 2 papers, 1 papers with code

Multimodal Motion Conditioned Diffusion Model for Skeleton-based Video Anomaly Detection

1 code implementation • ICCV 2023 • Alessandro Flaborea, Luca Collorone, Guido D'Amely, Stefano D'arrigo, Bardh Prenkaj, Fabio Galasso

Leading OCC techniques constrain the latent representations of normal motions to limited volumes and detect as abnormal anything outside, which accounts satisfactorily for the openset'ness of anomalies.

Ranked #1 on Video Anomaly Detection on HR-UBnormal

2D Human Pose Estimation Human Pose Forecasting +2

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Contracting Skeletal Kinematics for Human-Related Video Anomaly Detection

no code implementations • 23 Jan 2023 • Alessandro Flaborea, Guido D'Amely, Stefano D'arrigo, Marco Aurelio Sterpa, Alessio Sampieri, Fabio Galasso

Detecting the anomaly of human behavior is paramount to timely recognizing endangering situations, such as street fights or elderly falls.

Ranked #3 on Video Anomaly Detection on HR-UBnormal

Anomaly Detection Open Set Learning +1

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