activity
20152021
most citedRVOS: End-to-End Recurrent Network for Video Object Segmentation

37 citations · 80 across the 7 of their papers we have counts for

collaborators

14 papers

cs.CV20211 cited

Revamping Cross-Modal Recipe Retrieval with Hierarchical Transformers and Self-supervised Learning

Amaia Salvador, Erhan Gundogdu, Loris Bazzani +1

Cross-modal recipe retrieval has recently gained substantial attention due to the importance of food in people's lives, as well as the availability of vast amounts of digital cooki…

cs.CV2020

Mask-guided sample selection for Semi-Supervised Instance Segmentation

Miriam Bellver, Amaia Salvador, Jordi Torres +1

Image segmentation methods are usually trained with pixel-level annotations, which require significant human effort to collect. The most common solution to address this constraint…

cs.CV2019

WiCV 2019: The Sixth Women In Computer Vision Workshop

Irene Amerini, Elena Balashova, Sayna Ebrahimi +3

In this paper we present the Women in Computer Vision Workshop - WiCV 2019, organized in conjunction with CVPR 2019. This event is meant for increasing the visibility and inclusion…

cs.CV201923 cited

Budget-aware Semi-Supervised Semantic and Instance Segmentation

Miriam Bellver, Amaia Salvador, Jordi Torres +1

Methods that move towards less supervised scenarios are key for image segmentation, as dense labels demand significant human intervention. Generally, the annotation burden is mitig…

cs.CV2019

Elucidating image-to-set prediction: An analysis of models, losses and datasets

Luis Pineda, Amaia Salvador, Michal Drozdzal +1

In this paper, we identify an important reproducibility challenge in the image-to-set prediction literature that impedes proper comparisons among published methods, namely, researc…

cs.MM20199 cited

Wav2Pix: Speech-conditioned Face Generation using Generative Adversarial Networks

Amanda Duarte, Francisco Roldan, Miquel Tubau +7

Speech is a rich biometric signal that contains information about the identity, gender and emotional state of the speaker. In this work, we explore its potential to generate face i…