Ponències/Comunicacions de congressos
Recent Submissions
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Digitally stained confocal microscopy through deep learning
(Microtome Publishing, 2019)
Conference report
Open AccessSpecialists have used confocal microscopy in the ex-vivo modality to identify Basal Cell Carcinoma tumors with an overall sensitivity of 96.6% and specificity of 89.2% (Chung et al., 2004). However, this technology hasn’t ... -
Wav2Pix: speech-conditioned face generation using generative adversarial networks
(Institute of Electrical and Electronics Engineers (IEEE), 2019)
Conference lecture
Restricted access - publisher's policySpeech 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 images of a speaker by conditioning a ... -
RVOS: end-to-end recurrent network for video object segmentation
(Computer Vision Foundation, 2019)
Conference lecture
Open AccessMultiple 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. ... -
Inverse cooking: recipe generation from food images
(Computer Vision Foundation, 2019)
Conference report
Open AccessPeople 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 do not have access to its preparation ... -
Assessing knee OA severity with CNN attention-based end-to-end architectures
(2019)
Conference lecture
Open AccessThis 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 incorporates trainable attention modules ... -
One shot learning for generic instance segmentation in RGBD videos
(Scitepress, 2019)
Conference report
Open AccessHand-crafted features employed in classical generic instance segmentation methods have limited discriminative power to distinguish different objects in the scene, while Convolutional Neural Networks (CNNs) based semantic ... -
Linking media: adopting semantic technologies for multimodal media connection
(CEUR-WS.org, 2018)
Conference report
Open AccessToday's media and news organizations are constantly generating large amounts of multimedia content, majorly delivered online. As the online media market grows, the management and delivery of contents is becoming a challenge. ... -
SLAM-based 3D outdoor reconstructions from lidar data
(Institute of Electrical and Electronics Engineers (IEEE), 2018)
Conference report
Open AccessThe use of depth (RGBD) cameras to reconstruct large outdoor environments is not feasible due to lighting conditions and low depth range. LIDAR sensors can be used instead. Most state of the art SLAM methods are devoted ... -
PathGAN: visual scanpath prediction with generative adversarial networks
(Springer, 2019)
Conference lecture
Restricted access - publisher's policyWe 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 image defined by a human observer with its ... -
Collaborative voting of 3D features for robust gesture estimation
(Institute of Electrical and Electronics Engineers (IEEE), 2017)
Conference lecture
Open AccessHuman body analysis raises special interest because it enables a wide range of interactive applications. In this paper we present a gesture estimator that discriminates body poses in depth images. A novel collaborative ... -
Cross-modal embeddings for video and audio retrieval
(Springer, 2019)
Conference report
Open AccessIn this work, we explore the multi-modal information provided by the Youtube-8M dataset by projecting the audio and visual features into a common feature space, to obtain joint audio-visual embeddings. These links are used ... -
Action tube extraction based 3D-CNN for RGB-D action recognition
(Institute of Electrical and Electronics Engineers (IEEE), 2018)
Conference report
Open AccessIn this paper we propose a novel action tube extractor for RGB-D action recognition in trimmed videos. The action tube extractor takes as input a video and outputs an action tube. The method consists of two parts: spatial ...
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