activity
20212026
most citedLength-Aware Motion Synthesis via Latent Diffusion

2 citations · 4 across the 11 of their papers we have counts for

collaborators
Showing cs.CVShow all

8 papers · 1 filter

cs.CV2025

Video Unlearning via Low-Rank Refusal Vector

Simone Facchiano, Stefano Saravalle, Matteo Migliarini +7

Video generative models achieve high-quality synthesis from natural-language prompts by leveraging large-scale web data. However, this training paradigm inherently exposes them to…

cs.CV2025

Human Motion Unlearning

Edoardo De Matteis, Matteo Migliarini, Alessio Sampieri +2

We introduce Human Motion Unlearning and motivate it through the concrete task of preventing violent 3D motion synthesis, an important safety requirement given that popular text-to…

cs.CV2024

Social EgoMesh Estimation

Luca Scofano, Alessio Sampieri, Edoardo De Matteis +2

Accurately estimating the 3D pose of the camera wearer in egocentric video sequences is crucial to modeling human behavior in virtual and augmented reality applications. The task p…

cs.CV20242 cited

Length-Aware Motion Synthesis via Latent Diffusion

Alessio Sampieri, Alessio Palma, Indro Spinelli +1

The target duration of a synthesized human motion is a critical attribute that requires modeling control over the motion dynamics and style. Speeding up an action performance is no…

cs.CV2023

Staged Contact-Aware Global Human Motion Forecasting

Luca Scofano, Alessio Sampieri, Elisabeth Schiele +3

Scene-aware global human motion forecasting is critical for manifold applications, including virtual reality, robotics, and sports. The task combines human trajectory and pose fore…

cs.CV20231 cited

Best Practices for 2-Body Pose Forecasting

Muhammad Rameez Ur Rahman, Luca Scofano, Edoardo De Matteis +3

The task of collaborative human pose forecasting stands for predicting the future poses of multiple interacting people, given those in previous frames. Predicting two people in int…