1 code implementation • 31 Jan 2025 • Javier Montalvo, Pablo Carballeira, Álvaro García-Martín
In this work, we present a modified CARLA simulator designed with LiDAR semantic segmentation in mind, with new classes, more consistent object labeling with their counterparts from real datasets such as SemanticKITTI, and the possibility to adjust the object class distribution.
no code implementations • 4 Jan 2025 • Javier Montalvo, Álvaro García-Martín, Pablo Carballeira, Juan C. SanMiguel
To mitigate this cost there has been a surge in the use of synthetically generated data -- usually created using simulators or videogames -- which, in combination with domain adaptation methods, can effectively learn how to segment real data.
no code implementations • 21 Dec 2024 • Javier Montalvo, Roberto Alcover-Couso, Pablo Carballeira, Álvaro García-Martín, Juan C. SanMiguel, Marcos Escudero-Viñolo
This paper introduces a novel synthetic dataset that captures urban scenes under a variety of weather conditions, providing pixel-perfect, ground-truth-aligned images to facilitate effective feature alignment across domains.
1 code implementation • 5 Oct 2024 • Juan Ignacio Bravo Pérez-Villar, Álvaro García-Martín, Jesús Bescós, Juan C. SanMiguel
Due to the difficulty of replicating the real conditions during training, supervised algorithms for spacecraft pose estimation experience a drop in performance when trained on synthetic data and applied to real operational data.
1 code implementation • Applied Intelligence 2024 • Kirill Sirotkin, Marcos Escudero-Viñolo, Pablo Carballeira, Álvaro García-Martín
At a cost of extra training of only 0. 16% model parameters, in case of ResNet-50, we acquire a proxy task that (i) has a stronger correlation with end-to-end finetuned performance, (ii) improves the linear probing performance in the many- and few-shot learning regimes and (iii) in some cases, outperforms both linear probing and end-to-end finetuning, reaching the state-of-the-art performance on a pathology dataset.
Ranked #1 on
Classification
on MHIST
(using extra training data)
1 code implementation • 11 Jun 2024 • Javier Montalvo, Juan Ignacio Bravo Pérez-Villar, Álvaro García-Martín, Pablo Carballeira, Jesús Bescós
To address these limitations, we present SPIN (SPacecraft Imagery for Navigation), an open-source spacecraft image generation tool designed to support a wide range of visual navigation scenarios in space, with a particular focus on relative navigation tasks.
1 code implementation • 27 Dec 2022 • Juan Ignacio Bravo Pérez-Villar, Álvaro García-Martín, Jesús Bescós
Spacecraft pose estimation is a key task to enable space missions in which two spacecrafts must navigate around each other.
1 code implementation • 5 Sep 2019 • Alejandro López-Cifuentes, Marcos Escudero-Viñolo, Jesús Bescós, Álvaro García-Martín
Scene recognition is currently one of the top-challenging research fields in computer vision.
Ranked #1 on
Scene Recognition
on ADE20K