161 citations · 491 across the 9 of their papers we have counts for
10 papers
Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills
Víctor Campos, Alexander Trott, Caiming Xiong +3
Acquiring abilities in the absence of a task-oriented reward function is at the frontier of reinforcement learning research. This problem has been studied through the lens of empow…
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…
Assessing Knee OA Severity with CNN attention-based end-to-end architectures
Marc Górriz, Joseph Antony, Kevin McGuinness +2
This work proposes a novel end-to-end convolutional neural network (CNN) architecture to automatically quantify the severity of knee osteoarthritis (OA) using X-Ray images, which i…
Simple vs complex temporal recurrences for video saliency prediction
Panagiotis Linardos, Eva Mohedano, Juan Jose Nieto +3
This paper investigates modifying an existing neural network architecture for static saliency prediction using two types of recurrences that integrate information from the temporal…
PathGAN: Visual Scanpath Prediction with Generative Adversarial Networks
Marc Assens, Xavier Giro-i-Nieto, Kevin McGuinness +1
We introduce PathGAN, a deep neural network for visual scanpath prediction trained on adversarial examples. A visual scanpath is defined as the sequence of fixation points over an…
Saliency Weighted Convolutional Features for Instance Search
Eva Mohedano, Kevin McGuinness, Xavier Giro-i-Nieto +1
This work explores attention models to weight the contribution of local convolutional representations for the instance search task. We present a retrieval framework based on bags o…
SaltiNet: Scan-path Prediction on 360 Degree Images using Saliency Volumes
Marc Assens, Kevin McGuinness, Xavier Giro-i-Nieto +1
We introduce SaltiNet, a deep neural network for scanpath prediction trained on 360-degree images. The model is based on a temporal-aware novel representation of saliency informati…
Bags of Local Convolutional Features for Scalable Instance Search
Eva Mohedano, Amaia Salvador, Kevin McGuinness +3
This work proposes a simple instance retrieval pipeline based on encoding the convolutional features of CNN using the bag of words aggregation scheme (BoW). Assigning each local ar…
Shallow and Deep Convolutional Networks for Saliency Prediction
Junting Pan, Kevin McGuinness, Elisa Sayrol +2
The prediction of salient areas in images has been traditionally addressed with hand-crafted features based on neuroscience principles. This paper, however, addresses the problem w…
Exploring EEG for Object Detection and Retrieval
Eva Mohedano, Amaia Salvador, Sergi Porta +5
This paper explores the potential for using Brain Computer Interfaces (BCI) as a relevance feedback mechanism in content-based image retrieval. We investigate if it is possible to…