Publications de Pablo Marquez Neila

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Deep networks such as the U-Net are outstanding at segmenting biomedical images when enough training data is available, but only then. Here we introduce a Domain Adaptation approach that relies on two coupled U-Nets that either regularize or share correspo ...

Delineation of curvilinear structures is an important problem in Computer Vision with multiple practical applications. With the advent of Deep Learning, many current approaches on automatic delineation have focused on finding more powerful deep architectur ...

Size uniformity is one of the prominent features of superpixels. However, size uniformity rarely conforms to the varying content of an image. The chosen size of the superpixels therefore represents a compromise - how to obtain the fewest superpixels withou ...

Detection of surgical instruments plays a key role in ensuring patient safety in minimally invasive surgery. In this paper, we present a novel method for 2D vision-based recognition and pose estimation of surgical instruments that generalizes to different ...

Pablo Marquez Neila

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A Domain-Adaptive Two-Stream U-Net For Electron Microscopy Image Segmentation

A Domain-Adaptive Two-Stream U-Net for Electron Microscopy Image Segmentation

Beyond the Pixel-Wise Loss for Topology-Aware Delineation

Scale-Adaptive Superpixels

Simultaneous Recognition and Pose Estimation of Instruments in Minimally Invasive Surgery

Imposing Hard Constraints on Deep Networks: Promises and Limitations

Learning to Fuse 2D and 3D Image Cues for Monocular Body Pose Estimation