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Abel Gonzalez-Garcia

9 accepted papers

2020

MineGAN: Effective Knowledge Transfer From GANs to Target Domains With Few Images

Yaxing Wang, Abel Gonzalez-Garcia, David Berga, Luis Herranz, Fahad Shahbaz Khan, Joost van de Weijer
CVPR 2020poster

One of the attractive characteristics of deep neural networks is their ability to transfer knowledge obtained in one domain to other related domains. As a result, high-quality networks can be trained in domains with relatively little training data. This property has been extensively studied for disc…

Cited by 229PDF ↗code ↗Scholar ↗
2020

Orderless Recurrent Models for Multi-Label Classification

Vacit Oguz Yazici, Abel Gonzalez-Garcia, Arnau Ramisa, Bartlomiej Twardowski, Joost van de Weijer
CVPR 2020poster

Recurrent neural networks (RNN) are popular for many computer vision tasks, including multi-label classification. Since RNNs produce sequential outputs, labels need to be ordered for the multi-label classification task. Current approaches sort labels according to their frequency, typically ordering…

Cited by 131PDF ↗code ↗Scholar ↗
2020

Semi-Supervised Learning for Few-Shot Image-to-Image Translation

Yaxing Wang, Salman Khan, Abel Gonzalez-Garcia, Joost van de Weijer, Fahad Shahbaz Khan
CVPR 2020poster

In the last few years, unpaired image-to-image translation has witnessed Remarkable progress. Although the latest methods are able to generate realistic images, they crucially rely on a large number of labeled images. Recently, some methods have tackled the challenging setting of few-shot image-to-i…

Cited by 62PDF ↗code ↗Scholar ↗
2019

Active Learning for Deep Detection Neural Networks

Hamed H. Aghdam, Abel Gonzalez-Garcia, Joost van de Weijer, Antonio M. Lopez
ICCV 2019poster

The cost of drawing object bounding boxes (i.e. labeling) for millions of images is prohibitively high. For instance, labeling pedestrians in a regular urban image could take 35 seconds on average. Active learning aims to reduce the cost of labeling by selecting only those images that are informativ…

Cited by 176PDF ↗code ↗Scholar ↗
2019

Learning the Model Update for Siamese Trackers

Lichao Zhang, Abel Gonzalez-Garcia, Joost van de Weijer, Martin Danelljan, Fahad Shahbaz Khan
ICCV 2019poster

Siamese approaches address the visual tracking problem by extracting an appearance template from the current frame, which is used to localize the target in the next frame. In general, this template is linearly combined with the accumulated template from the previous frame, resulting in an exponentia…

Cited by 461PDF ↗code ↗Scholar ↗
2018

Image-to-image translation for cross-domain disentanglement

Abel Gonzalez-Garcia, Joost van de Weijer, Yoshua Bengio
NeurIPS 2018poster

Deep image translation methods have recently shown excellent results, outputting high-quality images covering multiple modes of the data distribution. There has also been increased interest in disentangling the internal representations learned by deep methods to further improve their performance and…

Cited by 487Source ↗PDF ↗code ↗Scholar ↗
2018

Transferring GANs: generating images from limited data

Yaxing Wang, Chenshen Wu, Luis Herranz, Joost van de Weijer, Abel Gonzalez-Garcia, Bogdan Raducanu
ECCV 2018poster

Transferring the knowledge of pretrained networks to new domains by means of finetuning is a widely used practice for applications based on discriminative models. To the best of our knowledge this practice has not been studied within the context of generative deep networks. Therefore, we study domai…

Cited by 393Source ↗PDF ↗code ↗Scholar ↗
2015

An Active Search Strategy for Efficient Object Class Detection

Abel Gonzalez-Garcia, Alexander Vezhnevets, Vittorio Ferrari
CVPR 2015poster

Object class detectors typically apply a window classifier to all the windows in a large set, either in a sliding window manner or using object proposals. In this paper, we develop an active search strategy that sequentially chooses the next window to evaluate based on all the information gathered b…

Cited by 84Source ↗PDF ↗Scholar ↗