no code implementations • 1 Nov 2019 • Marc Maceira, David Varas, Josep-Ramon Morros, JavierRuiz-Hidalgo, Ferran Marques
Depth data has a widespread use since the popularity of high-resolution 3D sensors.
1 code implementation • CVPR 2019 • Carles Ventura, Miriam Bellver, Andreu Girbau, Amaia Salvador, Ferran Marques, Xavier Giro-i-Nieto
Multiple object video object segmentation is a challenging task, specially for the zero-shot case, when no object mask is given at the initial frame and the model has to find the objects to be segmented along the sequence.
Ranked #1 on One-shot visual object segmentation on YouTube-VOS
1 code implementation • 2 Dec 2017 • Amaia Salvador, Miriam Bellver, Victor Campos, Manel Baradad, Ferran Marques, Jordi Torres, Xavier Giro-i-Nieto
We present a recurrent model for semantic instance segmentation that sequentially generates binary masks and their associated class probabilities for every object in an image.
1 code implementation • 11 Nov 2016 • Miriam Bellver, Xavier Giro-i-Nieto, Ferran Marques, Jordi Torres
We argue that, while this loss seems unavoidable when working with large amounts of object candidates, the much more reduced amount of region proposals generated by our reinforcement learning agent allows considering to extract features for each location without sharing convolutional computation among regions.
3 code implementations • 29 Apr 2016 • Amaia Salvador, Xavier Giro-i-Nieto, Ferran Marques, Shin'ichi Satoh
This work explores the suitability for instance retrieval of image- and region-wise representations pooled from an object detection CNN such as Faster R-CNN.
2 code implementations • 15 Apr 2016 • Eva Mohedano, Amaia Salvador, Kevin McGuinness, Ferran Marques, Noel E. O'Connor, Xavier Giro-i-Nieto
This work proposes a simple instance retrieval pipeline based on encoding the convolutional features of CNN using the bag of words aggregation scheme (BoW).
no code implementations • ICCV 2015 • David Varas, Mónica Alfaro, Ferran Marques
This paper presents a co-clustering technique that, given a collection of images and their hierarchies, clusters nodes from these hierarchies to obtain a coherent multiresolution representation of the image collection.
1 code implementation • 3 Mar 2015 • Jordi Pont-Tuset, Pablo Arbelaez, Jonathan T. Barron, Ferran Marques, Jitendra Malik
We propose a unified approach for bottom-up hierarchical image segmentation and object proposal generation for recognition, called Multiscale Combinatorial Grouping (MCG).
no code implementations • CVPR 2014 • Pablo Arbelaez, Jordi Pont-Tuset, Jonathan T. Barron, Ferran Marques, Jitendra Malik
We propose a unified approach for bottom-up hierarchical image segmentation and object candidate generation for recognition, called Multiscale Combinatorial Grouping (MCG).
no code implementations • CVPR 2014 • David Varas, Ferran Marques
We present a video object segmentation approach that extends the particle filter to a region-based image representation.
no code implementations • CVPR 2013 • Jordi Pont-Tuset, Ferran Marques
First, it surveys and structures the measures used to compare the segmentation results with a ground truth database; and proposes a new measure: the precision-recall for objects and parts.