activity
20232025
most citedMultimodal Motion Conditioned Diffusion Model for Skeleton-based Video Anomaly Detection

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.GR2025

PhysTalk: Language-driven Real-time Physics in 3D Gaussian Scenes

Luca Collorone, Mert Kiray, Indro Spinelli +2

Realistic visual simulations are omnipresent, yet their creation requires computing time, rendering, and expert animation knowledge. Open-vocabulary visual effects generation from…

cs.CV2025

MonSTeR: a Unified Model for Motion, Scene, Text Retrieval

Luca Collorone, Matteo Gioia, Massimiliano Pappa +5

Intention drives human movement in complex environments, but such movement can only happen if the surrounding context supports it. Despite the intuitive nature of this mechanism, e…

cs.CV2025

ANTHROPOS-V: benchmarking the novel task of Crowd Volume Estimation

Luca Collorone, Stefano D'Arrigo, Massimiliano Pappa +3

We introduce the novel task of Crowd Volume Estimation (CVE), defined as the process of estimating the collective body volume of crowds using only RGB images. Besides event managem…

cs.CV2024

MoDiPO: text-to-motion alignment via AI-feedback-driven Direct Preference Optimization

Massimiliano Pappa, Luca Collorone, Giovanni Ficarra +2

Diffusion Models have revolutionized the field of human motion generation by offering exceptional generation quality and fine-grained controllability through natural language condi…

cs.CV2023★ 1 cited

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

Alessandro Flaborea, Luca Collorone, Guido D'Amely +3

Anomalies are rare and anomaly detection is often therefore framed as One-Class Classification (OCC), i.e. trained solely on normalcy. Leading OCC techniques constrain the latent r…