Universitat Autònoma de Barcelona

research

∙ 10/05/2019

Kornia: an Open Source Differentiable Computer Vision Library for PyTorch

This work presents Kornia -- an open source computer vision library whic...

Edgar Riba, et al. ∙

research

∙ 05/28/2020

Early Screening of SARS-CoV-2 by Intelligent Analysis of X-Ray Images

Future SARS-CoV-2 virus outbreak COVID-XX might possibly occur during th...

D. Gil, et al. ∙

research

∙ 10/09/2019

Exploring Hate Speech Detection in Multimodal Publications

In this work we target the problem of hate speech detection in multimoda...

Raul Gomez, et al. ∙

research

∙ 02/13/2020

Continual Universal Object Detection

Object detection has improved significantly in recent years on multiple ...

Xialei Liu, et al. ∙

research

∙ 03/05/2020

GANwriting: Content-Conditioned Generation of Styled Handwritten Word Images

Although current image generation methods have reached impressive qualit...

Lei Kang, et al. ∙

research

∙ 09/04/2019

Dense Extreme Inception Network: Towards a Robust CNN Model for Edge Detection

This paper proposes a Deep Learning based edge detector, which is inspir...

Xavier Soria, et al. ∙

research

∙ 12/20/2019

TreyNet: A Neural Model for Text Localization, Transcription and Named Entity Recognition in Full Pages

In the last years, the consolidation of deep neural network architecture...

Manuel Carbonell, et al. ∙

research

∙ 11/20/2019

Active Learning for Deep Detection Neural Networks

The cost of drawing object bounding boxes (i.e. labeling) for millions o...

Hamed H. Aghdam, et al. ∙

research

∙ 06/10/2020

Simple and effective localized attribute representations for zero-shot learning

Zero-shot learning (ZSL) aims to discriminate images from unseen classes...

Shiqi Yang, et al. ∙

research

∙ 09/06/2018

Memory Replay GANs: learning to generate images from new categories without forgetting

Previous works on sequential learning address the problem of forgetting ...

Chenshen Wu, et al. ∙

research

∙ 10/09/2021

Class-Balanced Active Learning for Image Classification

Active learning aims to reduce the labeling effort that is required to t...

Javad Zolfaghari Bengar, et al. ∙

research

∙ 08/27/2019

Global Planar Convolutions for improved context aggregation in Brain Tumor Segmentation

In this work, we introduce the Global Planar Convolution module as a bui...

Santi Puch, et al. ∙

research

∙ 08/30/2019

Temporal Coherence for Active Learning in Videos

Autonomous driving systems require huge amounts of data to train. Manual...

Javad Zolfaghari Bengar, et al. ∙

research

∙ 11/03/2021

Discriminator Synthesis: On reusing the other half of Generative Adversarial Networks

Generative Adversarial Networks have long since revolutionized the world...

Diego Porres, et al. ∙

research

∙ 09/17/2018

Learning Effective RGB-D Representations for Scene Recognition

Deep convolutional networks (CNN) can achieve impressive results on RGB ...

Xinhang Song, et al. ∙

research

∙ 03/08/2019

Mix and match networks: multi-domain alignment for unpaired image-to-image translation

This paper addresses the problem of inferring unseen cross-domain and cr...

Yaxing Wang, et al. ∙

research

∙ 11/22/2019

Orderless Recurrent Models for Multi-label Classification

Recurrent neural networks (RNN) are popular for many computer vision tas...

Vacit Oguz Yazici, et al. ∙

research

∙ 07/23/2019

Controlling biases and diversity in diverse image-to-image translation

The task of unpaired image-to-image translation is highly challenging du...

Yaxing Wang, et al. ∙

research

∙ 11/15/2021

Multi-Task Classification of Sewer Pipe Defects and Properties using a Cross-Task Graph Neural Network Decoder

The sewerage infrastructure is one of the most important and expensive i...

Joakim Bruslund Haurum, et al. ∙

research

∙ 08/01/2018

Saliency for Fine-grained Object Recognition in Domains with Scarce Training Data

This paper investigates the role of saliency to improve the classificati...

Carola Figueroa Flores, et al. ∙

research

∙ 11/15/2018

A Neurodynamical model of Saliency prediction in V1

Computations in the primary visual cortex (area V1 or striate cortex) ha...

David Berga, et al. ∙

research

∙ 01/07/2019

Self-Supervised Learning from Web Data for Multimodal Retrieval

Self-Supervised learning from multimodal image and text data allows deep...

Raul Gomez, et al. ∙

research

∙ 01/14/2020

Fine-grained Image Classification and Retrieval by Combining Visual and Locally Pooled Textual Features

Text contained in an image carries high-level semantics that can be expl...

Andrés Mafla, et al. ∙

research

∙ 08/19/2019

SDIT: Scalable and Diverse Cross-domain Image Translation

Recently, image-to-image translation research has witnessed remarkable p...

Yaxing Wang, et al. ∙

research

∙ 05/26/2020

Pay Attention to What You Read: Non-recurrent Handwritten Text-Line Recognition

The advent of recurrent neural networks for handwriting recognition mark...

Lei Kang, et al. ∙

research

∙ 12/23/2021

LaTr: Layout-Aware Transformer for Scene-Text VQA

We propose a novel multimodal architecture for Scene Text Visual Questio...

Ali Furkan Biten, et al. ∙

research

∙ 06/16/2022

PeQuENet: Perceptual Quality Enhancement of Compressed Video with Adaptation- and Attention-based Network

In this paper we propose a generative adversarial network (GAN) framewor...

Saiping Zhang, et al. ∙

research

∙ 05/24/2018

Image-to-image translation for cross-domain disentanglement

Deep image translation methods have recently shown excellent results, ou...

Abel Gonzalez-Garcia, et al. ∙

research

∙ 08/20/2018

Learning to Learn from Web Data through Deep Semantic Embeddings

In this paper we propose to learn a multimodal image and text embedding ...

Raul Gomez, et al. ∙

research

∙ 08/27/2018

Single Shot Scene Text Retrieval

Textual information found in scene images provides high level semantic i...

Lluis Gómez, et al. ∙

research

∙ 06/10/2021

Date Estimation in the Wild of Scanned Historical Photos: An Image Retrieval Approach

This paper presents a novel method for date estimation of historical pho...

Adrià Molina, et al. ∙

research

∙ 04/22/2020

Distributed Learning and Inference with Compressed Images

Modern computer vision requires processing large amounts of data, both w...

Sudeep Katakol, et al. ∙

research

∙ 05/30/2016

Does Multimodality Help Human and Machine for Translation and Image Captioning?

This paper presents the systems developed by LIUM and CVC for the WMT16 ...

Ozan Caglayan, et al. ∙

research

∙ 09/19/2017

Colour Terms: a Categorisation Model Inspired by Visual Cortex Neurons

Although it seems counter-intuitive, categorical colours do not exist as...

Arash Akbarinia, et al. ∙

research

∙ 09/04/2017

Domain-adaptive deep network compression

Deep Neural Networks trained on large datasets can be easily transferred...

Marc Masana, et al. ∙

research

∙ 08/24/2017

Review on Computer Vision Techniques in Emergency Situation

In emergency situations, actions that save lives and limit the impact of...

Laura Lopez-Fuentes, et al. ∙

research

∙ 04/10/2017

Pay Attention to Those Sets! Learning Quantification from Images

Major advances have recently been made in merging language and vision re...

Ionut Sorodoc, et al. ∙

research

∙ 07/26/2017

RankIQA: Learning from Rankings for No-reference Image Quality Assessment

We propose a no-reference image quality assessment (NR-IQA) approach tha...

Xialei Liu, et al. ∙

research

∙ 12/29/2016

From Virtual to Real World Visual Perception using Domain Adaptation -- The DPM as Example

Supervised learning tends to produce more accurate classifiers than unsu...

Antonio M. Lopez, et al. ∙

research

∙ 07/07/2017

SigNet: Convolutional Siamese Network for Writer Independent Offline Signature Verification

Offline signature verification is one of the most challenging tasks in b...

Sounak Dey, et al. ∙

research

∙ 07/05/2017

R-PHOC: Segmentation-Free Word Spotting using CNN

This paper proposes a region based convolutional neural network for segm...

Suman Ghosh, et al. ∙

research

∙ 06/05/2017

Visual attention models for scene text recognition

In this paper we propose an approach to lexicon-free recognition of text...

Suman K. Ghosh, et al. ∙

research

∙ 05/24/2017

Self-supervised learning of visual features through embedding images into text topic spaces

End-to-end training from scratch of current deep architectures for new c...

Lluis Gómez, et al. ∙

research

∙ 04/10/2017

R-Clustering for Egocentric Video Segmentation

In this paper, we present a new method for egocentric video temporal seg...

Estefania Talavera, et al. ∙

research

∙ 12/22/2015

SR-Clustering: Semantic Regularized Clustering for Egocentric Photo Streams Segmentation

While wearable cameras are becoming increasingly popular, locating relev...

Mariella Dimiccoli, et al. ∙

research

∙ 02/01/2017

Product Graph-based Higher Order Contextual Similarities for Inexact Subgraph Matching

Many algorithms formulate graph matching as an optimization of an object...

Anjan Dutta, et al. ∙

research

∙ 02/01/2017

Understanding trained CNNs by indexing neuron selectivity

The impressive performance and plasticity of convolutional neural networ...

Ivet Rafegas, et al. ∙

research

∙ 01/16/2017

Bandwidth limited object recognition in high resolution imagery

This paper proposes a novel method to optimize bandwidth usage for objec...

Laura Lopez-Fuentes, et al. ∙

research

∙ 12/03/2016

Ensembles of Generative Adversarial Networks

Ensembles are a popular way to improve results of discriminative CNNs. T...

Yaxing Wang, et al. ∙

research

∙ 12/02/2016

Procedural Generation of Videos to Train Deep Action Recognition Networks

Deep learning for human action recognition in videos is making significa...

César Roberto de Souza, et al. ∙

Universitat Autònoma de Barcelona

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