1 citations · 1 across the 1 of their papers we have counts for
5 papers
Heteroscedastic Diffusion for Multi-Agent Trajectory Modeling
Guillem Capellera, Antonio Rubio, Luis Ferraz +1
Multi-agent trajectory modeling traditionally focuses on forecasting, often neglecting more general tasks like trajectory completion, which is essential for real-world applications…
JointDiff: Bridging Continuous and Discrete in Multi-Agent Trajectory Generation
Guillem Capellera, Luis Ferraz, Antonio Rubio +2
Generative models often treat continuous data and discrete events as separate processes, creating a gap in modeling complex systems where they interact synchronously. To bridge thi…
Multi-Modal Soccer Scene Analysis with Masked Pre-Training
Marc Peral, Guillem Capellera, Luis Ferraz +2
In this work we propose a multi-modal architecture for analyzing soccer scenes from tactical camera footage, with a focus on three core tasks: ball trajectory inference, ball state…
Unified Uncertainty-Aware Diffusion for Multi-Agent Trajectory Modeling
Guillem Capellera, Antonio Rubio, Luis Ferraz +1
Multi-agent trajectory modeling has primarily focused on forecasting future states, often overlooking broader tasks like trajectory completion, which are crucial for real-world app…
TranSPORTmer: A Holistic Approach to Trajectory Understanding in Multi-Agent Sports
Guillem Capellera, Luis Ferraz, Antonio Rubio +2
Understanding trajectories in multi-agent scenarios requires addressing various tasks, including predicting future movements, imputing missing observations, inferring the status of…