no code implementations • 11 Oct 2022 • Nataniel Ruiz, Miriam Bellver, Timo Bolkart, Ambuj Arora, Ming C. Lin, Javier Romero, Raja Bala
Training of BMnet is performed on data from real human subjects, and augmented with a novel adversarial body simulator (ABS) that finds and synthesizes challenging body shapes.
2 code implementations • 8 Jun 2021 • Ioannis Kazakos, Carles Ventura, Miriam Bellver, Carina Silberer, Xavier Giro-i-Nieto
Recent advances in deep learning have brought significant progress in visual grounding tasks such as language-guided video object segmentation.
2 code implementations • 1 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.
Ranked #1 on Referring Expression Segmentation on A2Dre test
no code implementations • 25 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.
no code implementations • 14 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.
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.
2 code implementations • 29 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.
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.