31 citations · 51 across the 3 of their papers we have counts for
16 papers · 1 filter
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…