1 citations · 1 across the 8 of their papers we have counts for
8 papers
Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and Benchmarks
Nobin Sarwar, Shubhashis Roy Dipta, Zheyuan Liu +1
With the growing adoption of VLMs, DMs, LLMs, and AFMs, these multimodal foundation models can inadvertently encode sensitive, copyrighted, biased, or unsafe cross-modal associatio…
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…
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…
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…
TI-PREGO: Chain of Thought and In-Context Learning for Online Mistake Detection in PRocedural EGOcentric Videos
Leonardo Plini, Luca Scofano, Edoardo De Matteis +6
Identifying procedural errors online from egocentric videos is a critical yet challenging task across various domains, including manufacturing, healthcare, and skill-based training…
PREGO: online mistake detection in PRocedural EGOcentric videos
Alessandro Flaborea, Guido Maria D'Amely di Melendugno, Leonardo Plini +5
Promptly identifying procedural errors from egocentric videos in an online setting is highly challenging and valuable for detecting mistakes as soon as they happen. This capability…
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…
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…