Search Results for author: Miriam Bellver

Found 8 papers, 6 papers with code

RefVOS: A Closer Look at Referring Expressions for Video Object Segmentation

2 code implementations1 Oct 2020 Miriam Bellver, Carles Ventura, Carina Silberer, Ioannis Kazakos, Jordi Torres, Xavier Giro-i-Nieto

The task of video object segmentation with referring expressions (language-guided VOS) is to, given a linguistic phrase and a video, generate binary masks for the object to which the phrase refers.

Referring Expression Segmentation Video Object Segmentation

Mask-guided sample selection for Semi-Supervised Instance Segmentation

no code implementations25 Aug 2020 Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto

Our method consists in first predicting pseudo-masks for the unlabeled pool of samples, together with a score predicting the quality of the mask.

Active Learning Instance Segmentation +2

Budget-aware Semi-Supervised Semantic and Instance Segmentation

no code implementations14 May 2019 Miriam Bellver, Amaia Salvador, Jordi Torres, Xavier Giro-i-Nieto

Methods that move towards less supervised scenarios are key for image segmentation, as dense labels demand significant human intervention.

Instance Segmentation Semantic Segmentation

RVOS: End-to-End Recurrent Network for Video Object Segmentation

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.

One-shot visual object segmentation Unsupervised Video Object Segmentation +1

Recurrent Neural Networks for Semantic Instance Segmentation

1 code implementation2 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.

Instance Segmentation Semantic Segmentation

Detection-aided liver lesion segmentation using deep learning

2 code implementations29 Nov 2017 Miriam Bellver, Kevis-Kokitsi Maninis, Jordi Pont-Tuset, Xavier Giro-i-Nieto, Jordi Torres, Luc van Gool

A fully automatic technique for segmenting the liver and localizing its unhealthy tissues is a convenient tool in order to diagnose hepatic diseases and assess the response to the according treatments.

Computed Tomography (CT) Lesion Segmentation

Hierarchical Object Detection with Deep Reinforcement Learning

1 code implementation11 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.

Object Detection Region Proposal

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