collaborators

5 papers

cs.CV2026

How You Move Tells What You'll Do: Trajectory-Conditioned Egocentric Prediction

Sejoon Jun, Hai Nguyen-Truong, Luigi Seminara +1

Predicting how a person's first-person view will evolve (what action will follow, what plan completes a task, whether an in-progress shot will score) is fundamentally under-specifi…

cs.CV2026

RECIPE: Procedural Planning via Grounding in Instructional Video

Luigi Seminara, Antonino Furnari, Lorenzo Torresani

Visual planning asks a model to generate the remaining steps of a procedure in natural language given a partial video context and a goal. Progress on this task is bottlenecked by a…

cs.CV2026

ViterbiPlanNet: Injecting Procedural Knowledge via Differentiable Viterbi for Planning in Instructional Videos

Luigi Seminara, Davide Moltisanti, Antonino Furnari

Procedural planning aims to predict a sequence of actions that transforms an initial visual state into a desired goal, a fundamental ability for intelligent agents operating in com…

cs.CV2025

Task Graph Maximum Likelihood Estimation for Procedural Activity Understanding in Egocentric Videos

Luigi Seminara, Giovanni Maria Farinella, Antonino Furnari

We introduce a gradient-based approach for learning task graphs from procedural activities, improving over hand-crafted methods. Our method directly optimizes edge weights via maxi…

cs.CV2025

Differentiable Task Graph Learning: Procedural Activity Representation and Online Mistake Detection from Egocentric Videos

Luigi Seminara, Giovanni Maria Farinella, Antonino Furnari

Procedural activities are sequences of key-steps aimed at achieving specific goals. They are crucial to build intelligent agents able to assist users effectively. In this context,…