LAMP

Category: CVPR

  • 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 Read Full Paper → 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 […]

  • Learning Metrics from Teachers: Compact Networks for Image Embedding

    Lu Yu, Vacit Oguz Yazici, Xialei Liu, Joost van de Weijer, Yongmei Cheng, Arnau Ramisa Read Full Paper → 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 use network distillation to efficiently compute image embeddings with small networks. Network […]

  • Mix and match networks: encoder-decoder alignment for zero-pair image translation

    Yaxing Wang, Joost van de Weijer, Luis Herranz Read Full Paper → We address the problem of image translation between domains or modalities for which no direct paired data is available (i.e. zero-pair translation). We propose mix and match networks, based on multiple encoders and decoders aligned in such a way that other encoder-decoder pairs can be […]

  • Leveraging Unlabeled Data for Crowd Counting by Learning to Rank

    Xialei Liu, Joost van de Weijer, Andrew D. Bagdanov Read Full Paper → We propose a novel crowd counting approach that leverages abundantly available unlabeled crowd imagery in a learning-to-rank framework. To induce a ranking of cropped images , we use the observation that any sub-image of a crowded scene image is guaranteed to contain the same […]

  • On the Duality Between Retinex and Image Dehazing

    Adrian Galdran, Aitor Alvarez-Gila, Alessandro Bria, Javier Vazquez-Corral, Marcelo Bertalmio Read Full Paper → Image dehazing deals with the removal of undesired loss of visibility in outdoor images due to the presence of fog. Retinex is a color vision model mimicking the ability of the Human Visual System to robustly discount varying illuminations when observing a scene under different […]

  • Objects as context for detecting their semantic parts

    Abel Gonzalez-Garcia, Davide Modolo, Vittorio Ferrari Read Full Paper → 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 also model the expected relative location of parts inside the objects based on their appearance. We achieve this with a […]

  • Unrolling loopy top-down semantic feedback in convolutional deep networks

    Carlo Gatta, Adriana Romero, Joost van de Weijer Read Full Paper → In this paper, we propose a novel way to perform top-down semantic feedback in convolutional deep networks for efficient and accurate image parsing. We also show how to add global appearance/semantic features, which have shown to improve image parsing performance in state-of-the-art methods, […]

  • Adaptive Color Attributes for Real-Time Visual Tracking

    Martin Danelljan, Fahad Shahbaz Khan, Michael Felsberg, Joost van de Weijer Read Full Paper → Visual tracking is a challenging problem in computer vision. Most state-of-the-art visual trackers either rely on luminance information or use simple color representations for image description. Contrary to visual tracking, for object recognition and detection, sophisticated color features when combined […]