activity
20182022
most citedSynthRef: Generation of Synthetic Referring Expressions for Object Segmentation

3 citations · 7 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV20221 cited

On the Complementarity of Images and Text for the Expression of Emotions in Social Media

Anna Khlyzova, Carina Silberer, Roman Klinger

Authors of posts in social media communicate their emotions and what causes them with text and images. While there is work on emotion and stimulus detection for each modality separ…

cs.CV20213 cited

SynthRef: Generation of Synthetic Referring Expressions for Object Segmentation

Ioannis Kazakos, Carles Ventura, Miriam Bellver +2

Recent advances in deep learning have brought significant progress in visual grounding tasks such as language-guided video object segmentation. However, collecting large datasets f…

cs.CV20201 cited

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

Miriam Bellver, Carles Ventura, Carina Silberer +3

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 t…

cs.CV20192 cited

Recurrent Instance Segmentation using Sequences of Referring Expressions

Alba Herrera-Palacio, Carles Ventura, Carina Silberer +3

The goal of this work is to segment the objects in an image that are referred to by a sequence of linguistic descriptions (referring expressions). We propose a deep neural network…

cs.CL2019

What do Entity-Centric Models Learn? Insights from Entity Linking in Multi-Party Dialogue

Laura Aina, Carina Silberer, Matthijs Westera +2

Humans use language to refer to entities in the external world. Motivated by this, in recent years several models that incorporate a bias towards learning entity representations ha…

cs.CL2018

AMORE-UPF at SemEval-2018 Task 4: BiLSTM with Entity Library

Laura Aina, Carina Silberer, Ionut-Teodor Sorodoc +2

This paper describes our winning contribution to SemEval 2018 Task 4: Character Identification on Multiparty Dialogues. It is a simple, standard model with one key innovation, an e…