87 citations · 699 across the 38 of their papers we have counts for
32 papers · 1 filter
Cost Savings from Automatic Quality Assessment of Generated Images
Xavier Giro-i-Nieto, Nefeli Andreou, Anqi Liang +3
Deep generative models have shown impressive progress in recent years, making it possible to produce high quality images with a simple text prompt or a reference image. However, st…
SIRA: Relightable Avatars from a Single Image
Pol Caselles, Eduard Ramon, Jaime Garcia +3
Recovering the geometry of a human head from a single image, while factorizing the materials and illumination is a severely ill-posed problem that requires prior information to be…
Topic Detection in Continuous Sign Language Videos
Alvaro Budria, Laia Tarres, Gerard I. Gallego +3
Significant progress has been made recently on challenging tasks in automatic sign language understanding, such as sign language recognition, translation and production. However, t…
H3D-Net: Few-Shot High-Fidelity 3D Head Reconstruction
Eduard Ramon, Gil Triginer, Janna Escur +4
Recent learning approaches that implicitly represent surface geometry using coordinate-based neural representations have shown impressive results in the problem of multi-view 3D re…
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…
Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data
Oscar Mañas, Alexandre Lacoste, Xavier Giro-i-Nieto +2
Remote sensing and automatic earth monitoring are key to solve global-scale challenges such as disaster prevention, land use monitoring, or tackling climate change. Although there…
Can Everybody Sign Now? Exploring Sign Language Video Generation from 2D Poses
Lucas Ventura, Amanda Duarte, Xavier Giro-i-Nieto
Recent work have addressed the generation of human poses represented by 2D/3D coordinates of human joints for sign language. We use the state of the art in Deep Learning for motion…
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…
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…
How2Sign: A Large-scale Multimodal Dataset for Continuous American Sign Language
Amanda Duarte, Shruti Palaskar, Lucas Ventura +5
One of the factors that have hindered progress in the areas of sign language recognition, translation, and production is the absence of large annotated datasets. Towards this end,…
Transcription-Enriched Joint Embeddings for Spoken Descriptions of Images and Videos
Benet Oriol, Jordi Luque, Ferran Diego +1
In this work, we propose an effective approach for training unique embedding representations by combining three simultaneous modalities: image and spoken and textual narratives. Th…
Hyperparameter-Free Losses for Model-Based Monocular Reconstruction
Eduard Ramon, Guillermo Ruiz, Thomas Batard +1
This work proposes novel hyperparameter-free losses for single view 3D reconstruction with morphable models (3DMM). We dispense with the hyperparameters used in other works by expl…
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…
RVOS: End-to-End Recurrent Network for Video Object Segmentation
Carles Ventura, Miriam Bellver, Andreu Girbau +3
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 o…
Inverse Cooking: Recipe Generation from Food Images
Amaia Salvador, Michal Drozdzal, Xavier Giro-i-Nieto +1
People enjoy food photography because they appreciate food. Behind each meal there is a story described in a complex recipe and, unfortunately, by simply looking at a food image we…
Temporal Saliency Adaptation in Egocentric Videos
Panagiotis Linardos, Eva Mohedano, Monica Cherto +2
This work adapts a deep neural model for image saliency prediction to the temporal domain of egocentric video. We compute the saliency map for each video frame, firstly with an off…
Online Detection of Action Start in Untrimmed, Streaming Videos
Zheng Shou, Junting Pan, Jonathan Chan +5
We aim to tackle a novel task in action detection - Online Detection of Action Start (ODAS) in untrimmed, streaming videos. The goal of ODAS is to detect the start of an action ins…
Recurrent Neural Networks for Semantic Instance Segmentation
Amaia Salvador, Miriam Bellver, Victor Campos +4
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. Our…
Detection-aided liver lesion segmentation using deep learning
Miriam Bellver, Kevis-Kokitsi Maninis, Jordi Pont-Tuset +3
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…
Cost-Effective Active Learning for Melanoma Segmentation
Marc Gorriz, Axel Carlier, Emmanuel Faure +1
We propose a novel Active Learning framework capable to train effectively a convolutional neural network for semantic segmentation of medical imaging, with a limited amount of trai…
More cat than cute? Interpretable Prediction of Adjective-Noun Pairs
Delia Fernandez, Alejandro Woodward, Victor Campos +3
The increasing availability of affect-rich multimedia resources has bolstered interest in understanding sentiment and emotions in and from visual content. Adjective-noun pairs (ANP…
Disentangling Motion, Foreground and Background Features in Videos
Xunyu Lin, Victor Campos, Xavier Giro-i-Nieto +2
This paper introduces an unsupervised framework to extract semantically rich features for video representation. Inspired by how the human visual system groups objects based on moti…
Class-Weighted Convolutional Features for Visual Instance Search
Albert Jimenez, Jose M. Alvarez, Xavier Giro-i-Nieto
Image retrieval in realistic scenarios targets large dynamic datasets of unlabeled images. In these cases, training or fine-tuning a model every time new images are added to the da…
Hierarchical Object Detection with Deep Reinforcement Learning
Miriam Bellver, Xavier Giro-i-Nieto, Ferran Marques +1
We present a method for performing hierarchical object detection in images guided by a deep reinforcement learning agent. The key idea is to focus on those parts of the image that…