no code implementations • CVPR 2014 • Luca Fiaschi, Ferran Diego, Konstantin Gregor, Martin Schiegg, Ullrich Koethe, Marta Zlatic, Fred A. Hamprecht
We use weakly supervised structured learning to track and disambiguate the identity of multiple indistinguishable, translucent and deformable objects that can overlap for many frames.
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.
no code implementations • CVPR 2016 • Ferran Diego, Fred A. Hamprecht
We propose a new way to train a structured output prediction model.
1 code implementation • NeurIPS 2017 • Sven Peter, Ferran Diego, Fred A. Hamprecht, Boaz Nadler
In contrast to previous approaches to learning with cost penalties, our method can grow very deep trees that on average are nonetheless cheap to compute.
1 code implementation • NeurIPS 2017 • Sven Peter, Elke Kirschbaum, Martin Both, Lee Campbell, Brandon Harvey, Conor Heins, Daniel Durstewitz, Ferran Diego, Fred A. Hamprecht
Cell assemblies, originally proposed by Donald Hebb (1949), are subsets of neurons firing in a temporally coordinated way that gives rise to repeated motifs supposed to underly neural representations and information processing.
no code implementations • 23 Oct 2018 • Radek Mackowiak, Philip Lenz, Omair Ghori, Ferran Diego, Oliver Lange, Carsten Rother
State of the art methods for semantic image segmentation are trained in a supervised fashion using a large corpus of fully labeled training images.
no code implementations • 18 Nov 2019 • Timo Milbich, Omair Ghori, Ferran Diego, Björn Ommer
To nevertheless find those relations which can be reliably utilized for learning, we follow a divide-and-conquer strategy: We find reliable similarities by extracting compact groups of images and reliable dissimilarities by partitioning these groups into subsets, converting the complicated overall problem into few reliable local subproblems.
no code implementations • 1 Jun 2020 • Benet Oriol, Jordi Luque, Ferran Diego, Xavier Giro-i-Nieto
In this work, we propose an effective approach for training unique embedding representations by combining three simultaneous modalities: image and spoken and textual narratives.
1 code implementation • 16 Apr 2021 • Biel Tura, Santiago Escuder, Ferran Diego, Carlos Segura, Jordi Luque
This work explores the application of Lambda networks, an alternative framework for capturing long-range interactions without attention, for the keyword spotting task.