no code implementations • 2 Apr 2024 • Carlos Plou, Nerea Gallego, Alberto Sabater, Eduardo Montijano, Pablo Urcola, Luis Montesano, Ruben Martinez-Cantin, Ana C. Murillo
Our novel pipeline is able to achieve high accuracy under these challenging conditions and incorporates a Bayesian approach (Laplace ensembles) to increase the robustness in the predictions, which is fundamental for medical applications.
no code implementations • 22 Nov 2022 • Alberto Sabater, Luis Montesano, Ana C. Murillo
Event cameras record sparse illumination changes with high temporal resolution and high dynamic range.
1 code implementation • 7 Apr 2022 • Alberto Sabater, Luis Montesano, Ana C. Murillo
Event cameras are sensors of great interest for many applications that run in low-resource and challenging environments.
1 code implementation • ICCV 2021 • Inigo Alonso, Alberto Sabater, David Ferstl, Luis Montesano, Ana C. Murillo
In an end-to-end training, the features from both labeled and unlabeled data are optimized to be similar to same-class samples from the memory bank.
1 code implementation • 3 Mar 2021 • Alberto Sabater, Iñigo Alonso, Luis Montesano, Ana C. Murillo
And, more importantly, when performing hand action recognition for action domains and camera perspectives which our approach has not been trained for (cross-domain action classification), our proposed framework achieves comparable performance to intra-domain state-of-the-art methods.
1 code implementation • 17 Feb 2021 • Alberto Sabater, Laura Santos, Jose Santos-Victor, Alexandre Bernardino, Luis Montesano, Ana C. Murillo
We also develop a set of complementary steps that boost the action recognition performance in the most challenging scenarios.
Ranked #4 on One-Shot 3D Action Recognition on NTU RGB+D 120
no code implementations • 23 Oct 2020 • Inigo Alonso, Luis Riazuelo, Luis Montesano, Ana C. Murillo
Besides, we propose a learning-based approach that aligns the distribution of the semantic classes of the target domain to the source domain.
1 code implementation • 1 Oct 2020 • Alberto Sabater, Luis Montesano, Ana C. Murillo
Object recognition in video is an important task for plenty of applications, including autonomous driving perception, surveillance tasks, wearable devices or IoT networks.
Ranked #18 on Video Object Detection on ImageNet VID
1 code implementation • 23 Sep 2020 • Alberto Sabater, Luis Montesano, Ana C. Murillo
Object recognition in video is an important task for plenty of applications, including autonomous driving perception, surveillance tasks, wearable devices or IoT networks.
no code implementations • 10 Sep 2020 • Alberto Sabater, Luis Montesano, Ana C. Murillo
This work studies the problem of object detection and localization on videos captured by this type of camera.
1 code implementation • 25 Feb 2020 • Iñigo Alonso, Luis Riazuelo, Luis Montesano, Ana C. Murillo
Fast and efficient semantic segmentation methods are needed to match the strong computational and temporal restrictions of many of these real-world applications.
Ranked #1 on Real-Time 3D Semantic Segmentation on SemanticKITTI
1 code implementation • CVPR 2019 • Jose M. Facil, Benjamin Ummenhofer, Huizhong Zhou, Luis Montesano, Thomas Brox, Javier Civera
Single-view depth estimation suffers from the problem that a network trained on images from one camera does not generalize to images taken with a different camera model.
no code implementations • 25 Feb 2019 • Jose M. Facil, Daniel Olid, Luis Montesano, Javier Civera
Visual place recognition is particularly challenging when places suffer changes in its appearance.
1 code implementation • 27 Nov 2017 • Giampiero Salvi, Luis Montesano, Alexandre Bernardino, José Santos-Victor
The model is based on an affordance network, i. e., a mapping between robot actions, robot perceptions, and the perceived effects of these actions upon objects.
no code implementations • 22 Nov 2016 • José M. Fácil, Alejo Concha, Luis Montesano, Javier Civera
The single and multi-view fusion we propose is challenging in several aspects.
no code implementations • 6 Mar 2014 • Manuel Lopes, Luis Montesano
In this survey we present different approaches that allow an intelligent agent to explore autonomous its environment to gather information and learn multiple tasks.