LAMP

Category: Publications

  • Review on computer vision techniques in emergency situations

    Laura Lopez-Fuentes, Joost van de Weijer, Manuel González-Hidalgo, Harald Skinnemoen & Andrew D. Bagdanov Read Full Paper → In emergency situations, actions that save lives and limit the impact of hazards are crucial. In order to act, situational awareness is needed to decide what to do. Geolocalized photos and video of the situations as they evolve can be crucial in […]

  • Adversarial Networks for Spatial Context-Aware Spectral Image Reconstruction from RGB

    Aitor Alvarez-Gila, Joost van de Weijer, Estibaliz Garrote Read Full Paper → Hyperspectral signal reconstruction aims at recovering the original spectral input that produced a certain trichromatic (RGB) response from a capturing device or observer. Given the heavily underconstrained, non-linear nature of the problem, traditional techniques leverage different statistical properties of the spectral signal in order to […]

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

    Xialei Liu, Joost van de Weijer, Andrew D. Bagdanov Read Full Paper → We propose a no-reference image quality assessment (NR-IQA) approach that learns from rankings (RankIQA). To address the problem of limited IQA dataset size, we train a Siamese Network to rank images in terms of image quality by using synthetically generated distortions for which relative […]

  • Domain-adaptive deep network compression

    Marc Masana, Joost van de Weijer, Luis Herranz, Andrew D. Bagdanov, Jose M Alvarez Read Full Paper → Deep Neural Networks trained on large datasets can be easily transferred to new domains with far fewer labeled examples by a process called fine-tuning. This has the advantage that representations learned in the large source domain can be exploited on smaller […]

  • 3D color charts for camera spectral sensitivity estimation

    R Deeb, D Muselet, M Hebert, A Tremeau, J van de Weijer, F ETIENNE Read Full Paper → Estimating spectral data such as camera sensor responses or illuminant spectral power distribution from raw RGB camera outputs is crucial in many computer vision applications. Usually, 2D color charts with various patches of known spectral reflectance are used as reference […]

  • LIUM-CVC Submissions for WMT17 Multimodal Translation Task

    Ozan Caglayan, Walid Aransa, Adrien Bardet, Mercedes García-Martínez, Fethi Bougares, Loïc Barrault, Marc Masana, Luis Herranz, Joost van de Weijer Read Full Paper → This paper describes the monomodal and multimodal Neural Machine Translation systems developed by LIUM and CVC for WMT17 Shared Task on Multimodal Translation. We mainly explored two multimodal architectures where either global visual features or convolutional feature maps are […]

  • Improved Recursive Geodesic Distance Computation for Edge Preserving Filter

    Mikhail G. Mozerov; Joost van de Weijer Read Full Paper → All known recursive filters based on the geodesic distance affinity are realized by two 1D recursions applied in two orthogonal directions of the image plane. The 2D extension of the filter is not valid and has theoretically drawbacks, which lead to known artifacts. In this […]

  • Bandwidth Limited Object Recognition in High Resolution Imagery

    Laura Lopez-Fuentes; Andrew D. Bagdanov; Joost Van De Weijer; Harald Skinnemoen Read Full Paper → This paper proposes a novel method to optimize bandwidth usage for object detection in critical communication scenarios. We develop two operating models of active information seeking. The first model identifies promising regions in low resolution imagery and progressively requests higher resolution regions on […]

  • Ensembles of Generative Adversarial Networks

    Yaxing Wang, Lichao Zhang, Joost van de Weijer Read Full Paper → Ensembles are a popular way to improve results of discriminative CNNs. The combination of several networks trained starting from different initializations improves results significantly. In this paper we investigate the usage of ensembles of GANs. The specific nature of GANs opens up several new ways […]

  • Invertible Conditional GANs for image editing

    Guim Perarnau, Joost van de Weijer, Bogdan Raducanu, Jose M. Álvarez Read Full Paper → Generative Adversarial Networks (GANs) have recently demonstrated to successfully approximate complex data distributions. A relevant extension of this model is conditional GANs (cGANs), where the introduction of external information allows to determine specific representations of the generated images. In this work, we evaluate […]