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    Chapter and Conference Paper

    Adversarially Robust Panoptic Segmentation (ARPaS) Benchmark

    We propose the Adversarially Robust Panoptic Segmentation (ARPaS) benchmark to assess the general robustness of panoptic segmentation techniques. To account for the differences between instance and semantic se...

    Laura Daza, Jordi Pont-Tuset, Pablo Arbeláez in Computer Vision – ECCV 2022 Workshops (2023)

  2. No Access

    Article

    The Open Images Dataset V4

    We present Open Images V4, a dataset of 9.2M images with unified annotations for image classification, object detection and visual relationship detection. The images have a Creative Commons Attribution license...

    Alina Kuznetsova, Hassan Rom, Neil Alldrin in International Journal of Computer Vision (2020)

  3. No Access

    Chapter and Conference Paper

    Connecting Vision and Language with Localized Narratives

    We propose Localized Narratives, a new form of multimodal image annotations connecting vision and language. We ask annotators to describe an image with their voice while simultaneously hovering their mouse ove...

    Jordi Pont-Tuset, Jasper Uijlings, Soravit Changpinyo in Computer Vision – ECCV 2020 (2020)

  4. Chapter and Conference Paper

    Iterative Deep Retinal Topology Extraction

    This paper tackles the task of estimating the topology of filamentary networks such as retinal vessels. Building on top of a global model that performs a dense semantical classification of the pixels of the im...

    Carles Ventura, Jordi Pont-Tuset in Patch-Based Techniques in Medical Imaging (2018)

  5. Chapter and Conference Paper

    Deep Retinal Image Understanding

    This paper presents Deep Retinal Image Understanding (DRIU), a unified framework of retinal image analysis that provides both retinal vessel and optic disc segmentation. We make use of deep Convolutional Neura...

    Kevis-Kokitsi Maninis, Jordi Pont-Tuset in Medical Image Computing and Computer-Assis… (2016)

  6. Chapter and Conference Paper

    Convolutional Oriented Boundaries

    We present Convolutional Oriented Boundaries (COB), which produces multiscale oriented contours and region hierarchies starting from generic image classification Convolutional Neural Networks (CNNs). COB is co...

    Kevis-Kokitsi Maninis, Jordi Pont-Tuset, Pablo Arbeláez in Computer Vision – ECCV 2016 (2016)