no code implementations • 10 Dec 2014 • José M. Álvarez, Ferran Diego, Joan Serrat, Antonio M. López
The major challenges of road detection are dealing with shadows and lighting variations and the presence of other objects in the scene.
1 code implementation • 16 Aug 2018 • Marc Masana, Idoia Ruiz, Joan Serrat, Joost Van de Weijer, Antonio M. Lopez
When neural networks process images which do not resemble the distribution seen during training, so called out-of-distribution images, they often make wrong predictions, and do so too confidently.
no code implementations • CVPR 2020 • Lorenzo Porzi, Markus Hofinger, Idoia Ruiz, Joan Serrat, Samuel Rota Bulò, Peter Kontschieder
Training MOTSNet with our automatically extracted data leads to significantly improved sMOTSA scores on the novel KITTI MOTS dataset (+1. 9%/+7. 5% on cars/pedestrians), and MOTSNet improves by +4. 1% over previously best methods on the MOTSChallenge dataset.
no code implementations • 12 Oct 2020 • Hannes Mueller, Andre Groger, Jonathan Hersh, Andrea Matranga, Joan Serrat
Existing data on building destruction in conflict zones rely on eyewitness reports or manual detection, which makes it generally scarce, incomplete and potentially biased.
no code implementations • 3 Jan 2021 • Idoia Ruiz, Lorenzo Porzi, Samuel Rota Bulò, Peter Kontschieder, Joan Serrat
We introduce the problem of weakly supervised Multi-Object Tracking and Segmentation, i. e. joint weakly supervised instance segmentation and multi-object tracking, in which we do not provide any kind of mask annotation.
no code implementations • 4 Dec 2023 • Mohammad Altillawi, Shile Li, Sai Manoj Prakhya, Ziyuan Liu, Joan Serrat
In this paper, we propose to utilize these minimal available labels (. i. e, poses) to learn the underlying 3D geometry of the scene and use the geometry to estimate the 6 DoF camera pose.