584 citations · 2.3k across the 78 of their papers we have counts for
13 papers · 1 filter
Variable Rate Deep Image Compression with Modulated Autoencoder
Fei Yang, Luis Herranz, Joost van de Weijer +3
Variable rate is a requirement for flexible and adaptable image and video compression. However, deep image compression methods are optimized for a single fixed rate-distortion trad…
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…
Self-supervised blur detection from synthetically blurred scenes
Aitor Alvarez-Gila, Adrian Galdran, Estibaliz Garrote +1
Blur detection aims at segmenting the blurred areas of a given image. Recent deep learning-based methods approach this problem by learning an end-to-end mapping between the blurred…
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),…
Learning Metrics from Teachers: Compact Networks for Image Embedding
Lu Yu, Vacit Oguz Yazici, Xialei Liu +3
Metric learning networks are used to compute image embeddings, which are widely used in many applications such as image retrieval and face recognition. In this paper, we propose to…
Mix and match networks: cross-modal alignment for zero-pair image-to-image translation
Yaxing Wang, Luis Herranz, Joost van de Weijer
This paper addresses the problem of inferring unseen cross-modal image-to-image translations between multiple modalities. We assume that only some of the pairwise translations have…
Exploiting Unlabeled Data in CNNs by Self-supervised Learning to Rank
Xialei Liu, Joost van de Weijer, Andrew D. Bagdanov
For many applications the collection of labeled data is expensive laborious. Exploitation of unlabeled data during training is thus a long pursued objective of machine learning. Se…