activity
20182026
most citedOn discrete symmetries of robotics systems: A group-theoretic and data-driven analysis

8 citations · 23 across the 11 of their papers we have counts for

collaborators
Showing cs.CVShow all

13 papers · 1 filter

cs.CV2026

Deformable Triangle Splatting: Flexible Primitives for Real-Time Radiance Field Rendering

Oriol Jiménez-Ayguadé, Antonio Agudo

Recent radiance field methods represent scenes with 2D primitives that offer surface alignment and efficient rasterization, from Gaussian disks to triangles, yet all rely on convex…

cs.CV2024

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…

cs.CV2024★ 1 cited

FootBots: A Transformer-based Architecture for Motion Prediction in Soccer

Guillem Capellera, Luis Ferraz, Antonio Rubio +2

Motion prediction in soccer involves capturing complex dynamics from player and ball interactions. We present FootBots, an encoder-decoder transformer-based architecture addressing…

cs.CV2023★ 1 cited

Robust Wind Turbine Blade Segmentation from RGB Images in the Wild

Raül Pérez-Gonzalo, Andreas Espersen, Antonio Agudo

With the relentless growth of the wind industry, there is an imperious need to design automatic data-driven solutions for wind turbine maintenance. As structural health monitoring…

cs.CV2022

Permutation-Invariant Relational Network for Multi-person 3D Pose Estimation

Nicolas Ugrinovic, Adria Ruiz, Antonio Agudo +2

The recovery of multi-person 3D poses from a single RGB image is a severely ill-conditioned problem due to the inherent 2D-3D depth ambiguity, inter-person occlusions, and body tru…

cs.CV2022★ 1 cited

Conditional-Flow NeRF: Accurate 3D Modelling with Reliable Uncertainty Quantification

Jianxiong Shen, Antonio Agudo, Francesc Moreno-Noguer +1

A critical limitation of current methods based on Neural Radiance Fields (NeRF) is that they are unable to quantify the uncertainty associated with the learned appearance and geome…