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  1. Article

    Open Access

    SRT3D: A Sparse Region-Based 3D Object Tracking Approach for the Real World

    Region-based methods have become increasingly popular for model-based, monocular 3D tracking of texture-less objects in cluttered scenes. However, while they achieve state-of-the-art results, most methods are ...

    Manuel Stoiber, Martin Pfanne, Klaus H. Strobl in International Journal of Computer Vision (2022)

  2. No Access

    Chapter and Conference Paper

    A Sparse Gaussian Approach to Region-Based 6DoF Object Tracking

    We propose a novel, highly efficient sparse approach to region-based 6DoF object tracking that requires only a monocular RGB camera and the 3D object model. The key contribution of our work is a probabilistic ...

    Manuel Stoiber, Martin Pfanne, Klaus H. Strobl in Computer Vision – ACCV 2020 (2021)

  3. No Access

    Article

    Augmented Autoencoders: Implicit 3D Orientation Learning for 6D Object Detection

    We propose a real-time RGB-based pipeline for object detection and 6D pose estimation. Our novel 3D orientation estimation is based on a variant of the Denoising Autoencoder that is trained on simulated views ...

    Martin Sundermeyer, Zoltan-Csaba Marton in International Journal of Computer Vision (2020)

  4. Chapter and Conference Paper

    Non-rigid 3D Shape Retrieval via Large Margin Nearest Neighbor Embedding

    In this paper, we propose a highly efficient metric learning approach to non-rigid 3D shape analysis. From a training set of 3D shapes from different classes, we learn a transformation of the shapes which opti...

    Ioannis Chiotellis, Rudolph Triebel, Thomas Windheuser in Computer Vision – ECCV 2016 (2016)

  5. No Access

    Chapter and Conference Paper

    Active Online Learning for Interactive Segmentation Using Sparse Gaussian Processes

    We present an active learning framework for image segmentation with user interaction. Our system uses a sparse Gaussian Process classifier (GPC) trained on manually labeled image pixels (user scribbles) and re...

    Rudolph Triebel, Jan Stühmer, Mohamed Souiai, Daniel Cremers in Pattern Recognition (2014)

  6. Chapter and Conference Paper

    Exploiting Repetitive Object Patterns for Model Compression and Completion

    Many man-made and natural structures consist of similar elements arranged in regular patterns. In this paper we present an unsupervised approach for discovering and reasoning on repetitive patterns of objects ...

    Luciano Spinello, Rudolph Triebel, Dizan Vasquez in Computer Vision – ECCV 2010 (2010)