181 citations · 373 across the 14 of their papers we have counts for
18 papers
Unsupervised Cross-Modal Distillation for Thermal Infrared Tracking
Jingxian Sun, Lichao Zhang, Yufei Zha +4
The target representation learned by convolutional neural networks plays an important role in Thermal Infrared (TIR) tracking. Currently, most of the top-performing TIR trackers ar…
MineGAN++: Mining Generative Models for Efficient Knowledge Transfer to Limited Data Domains
Yaxing Wang, Abel Gonzalez-Garcia, Chenshen Wu +4
GANs largely increases the potential impact of generative models. Therefore, we propose a novel knowledge transfer method for generative models based on mining the knowledge that i…
Semi-supervised Learning for Few-shot Image-to-Image Translation
Yaxing Wang, Salman Khan, Abel Gonzalez-Garcia +2
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…
MineGAN: effective knowledge transfer from GANs to target domains with few images
Yaxing Wang, Abel Gonzalez-Garcia, David Berga +3
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 netw…
Active Learning for Deep Detection Neural Networks
Hamed H. Aghdam, Abel Gonzalez-Garcia, Joost van de Weijer +1
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 se…
Orderless Recurrent Models for Multi-label Classification
Vacit Oguz Yazici, Abel Gonzalez-Garcia, Arnau Ramisa +2
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 f…
Learning the Model Update for Siamese Trackers
Lichao Zhang, Abel Gonzalez-Garcia, Joost van de Weijer +2
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 gener…
Temporal Coherence for Active Learning in Videos
Javad Zolfaghari Bengar, Abel Gonzalez-Garcia, Gabriel Villalonga +5
Autonomous driving systems require huge amounts of data to train. Manual annotation of this data is time-consuming and prohibitively expensive since it involves human resources. Th…
Multi-Modal Fusion for End-to-End RGB-T Tracking
Lichao Zhang, Martin Danelljan, Abel Gonzalez-Garcia +2
We propose an end-to-end tracking framework for fusing the RGB and TIR modalities in RGB-T tracking. Our baseline tracker is DiMP (Discriminative Model Prediction), which employs a…
SDIT: Scalable and Diverse Cross-domain Image Translation
Yaxing Wang, Abel Gonzalez-Garcia, Joost van de Weijer +1
Recently, image-to-image translation research has witnessed remarkable progress. Although current approaches successfully generate diverse outputs or perform scalable image transfe…
Controlling biases and diversity in diverse image-to-image translation
Yaxing Wang, Abel Gonzalez-Garcia, Joost van de Weijer +1
The task of unpaired image-to-image translation is highly challenging due to the lack of explicit cross-domain pairs of instances. We consider here diverse image translation (DIT),…
Measuring Semantic Abstraction of Multilingual NMT with Paraphrase Recognition and Generation Tasks
Jörg Tiedemann, Yves Scherrer
In this paper, we investigate whether multilingual neural translation models learn stronger semantic abstractions of sentences than bilingual ones. We test this hypotheses by measu…
Synthetic data generation for end-to-end thermal infrared tracking
Lichao Zhang, Abel Gonzalez-Garcia, Joost van de Weijer +2
The usage of both off-the-shelf and end-to-end trained deep networks have significantly improved performance of visual tracking on RGB videos. However, the lack of large labeled da…
Image-to-image translation for cross-domain disentanglement
Abel Gonzalez-Garcia, Joost van de Weijer, Yoshua Bengio
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…
Transferring GANs: generating images from limited data
Yaxing Wang, Chenshen Wu, Luis Herranz +3
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 ou…
Objects as context for detecting their semantic parts
Abel Gonzalez-Garcia, Davide Modolo, Vittorio Ferrari
We present a semantic part detection approach that effectively leverages object information.We use the object appearance and its class as indicators of what parts to expect. We als…
Do semantic parts emerge in Convolutional Neural Networks?
Abel Gonzalez-Garcia, Davide Modolo, Vittorio Ferrari
Semantic object parts can be useful for several visual recognition tasks. Lately, these tasks have been addressed using Convolutional Neural Networks (CNN), achieving outstanding r…
An active search strategy for efficient object class detection
Abel Gonzalez-Garcia, Alexander Vezhnevets, Vittorio Ferrari
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…