Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Centre National de la Recherche ScientifiqueFR1.2k papers
- The University of TokyoJP948 papers
- Excellence Cluster UniverseDE902 papers
- University of BonnDE857 papers
- Max Planck Institute for PhysicsDE848 papers
- Ludwig-Maximilians-Universität MünchenDE836 papers
- Lawrence Berkeley National LaboratoryUS774 papers
- University of CopenhagenDK774 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR757 papers
- Institut National de Physique Nucléaire et de Physique des ParticulesFR745 papers
- European Organization for Nuclear ResearchCH705 papers
- Istituto Nazionale di Fisica Nucleare, Sezione di TorinoIT682 papers
30 papers · 2 filters
ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans
Angela Dai, Daniel Ritchie, Martin Bokeloh +3
We introduce ScanComplete, a novel data-driven approach for taking an incomplete 3D scan of a scene as input and predicting a complete 3D model along with per-voxel semantic labels…
SUPRA: Open Source Software Defined Ultrasound Processing for Real-Time Applications
Rüdiger Göbl, Nassir Navab, Christoph Hennersperger
Research in ultrasound imaging is limited in reproducibility by two factors: First, many existing ultrasound pipelines are protected by intellectual property, rendering exchange of…
Brain Extraction from Normal and Pathological Images: A Joint PCA/Image-Reconstruction Approach
Xu Han, Roland Kwitt, Stephen Aylward +6
Brain extraction from images is a common pre-processing step. Many approaches exist, but they are frequently only designed to perform brain extraction from images without strong pa…
Deep learning in remote sensing: a review
Xiao Xiang Zhu, Devis Tuia, Lichao Mou +4
Standing at the paradigm shift towards data-intensive science, machine learning techniques are becoming increasingly important. In particular, as a major breakthrough in the field,…
Variational Methods for Normal Integration
Yvain Quéau, Jean-Denis Durou, Jean-François Aujol
The need for an efficient method of integration of a dense normal field is inspired by several computer vision tasks, such as shape-from-shading, photometric stereo, deflectometry,…
Normal Integration: A Survey
Yvain Quéau, Jean-Denis Durou, Jean-François Aujol
The need for efficient normal integration methods is driven by several computer vision tasks such as shape-from-shading, photometric stereo, deflectometry, etc. In the first part o…
Direct Pose Estimation with a Monocular Camera
Darius Burschka, Elmar Mair
We present a direct method to calculate a 6DoF pose change of a monocular camera for mobile navigation. The calculated pose is estimated up to a constant unknown scale parameter th…
A Variational Approach to Shape-from-shading Under Natural Illumination
Yvain Quéau, Jean Mélou, Fabien Castan +2
A numerical solution to shape-from-shading under natural illumination is presented. It builds upon an augmented Lagrangian approach for solving a generic PDE-based shape-from-shadi…
Associative Domain Adaptation
Philip Haeusser, Thomas Frerix, Alexander Mordvintsev +1
We propose associative domain adaptation, a novel technique for end-to-end domain adaptation with neural networks, the task of inferring class labels for an unlabeled target domain…
Model-based learning of local image features for unsupervised texture segmentation
Martin Kiechle, Martin Storath, Andreas Weinmann +1
Features that capture well the textural patterns of a certain class of images are crucial for the performance of texture segmentation methods. The manual selection of features or d…
LED-based Photometric Stereo: Modeling, Calibration and Numerical Solution
Yvain Quéau, Bastien Durix, Tao Wu +3
We conduct a thorough study of photometric stereo under nearby point light source illumination, from modeling to numerical solution, through calibration. In the classical formulati…
Learning without Prejudice: Avoiding Bias in Webly-Supervised Action Recognition
Christian Rupprecht, Ansh Kapil, Nan Liu +2
Webly-supervised learning has recently emerged as an alternative paradigm to traditional supervised learning based on large-scale datasets with manual annotations. The key idea is…
Alignment Distances on Systems of Bags
Alexander Sagel, Martin Kleinsteuber
Recent research in image and video recognition indicates that many visual processes can be thought of as being generated by a time-varying generative model. A nearby descriptive mo…
Segmentation of Intracranial Arterial Calcification with Deeply Supervised Residual Dropout Networks
Gerda Bortsova, Gijs van Tulder, Florian Dubost +5
Intracranial carotid artery calcification (ICAC) is a major risk factor for stroke, and might contribute to dementia and cognitive decline. Reliance on time-consuming manual annota…
Real-time Distracted Driver Posture Classification
Yehya Abouelnaga, Hesham M. Eraqi, Mohamed N. Moustafa
In this paper, we present a new dataset for "distracted driver" posture estimation. In addition, we propose a novel system that achieves 95.98% driving posture estimation classific…
A Multi-Armed Bandit to Smartly Select a Training Set from Big Medical Data
Benjamín Gutiérrez, Loïc Peter, Tassilo Klein +1
With the availability of big medical image data, the selection of an adequate training set is becoming more important to address the heterogeneity of different datasets. Simply inc…
Plan3D: Viewpoint and Trajectory Optimization for Aerial Multi-View Stereo Reconstruction
Benjamin Hepp, Matthias Nießner, Otmar Hilliges
We introduce a new method that efficiently computes a set of viewpoints and trajectories for high-quality 3D reconstructions in outdoor environments. Our goal is to automatically e…
Fusion of Head and Full-Body Detectors for Multi-Object Tracking
Roberto Henschel, Laura Leal-Taixé, Daniel Cremers +1
In order to track all persons in a scene, the tracking-by-detection paradigm has proven to be a very effective approach. Yet, relying solely on a single detector is also a major li…
Challenges in Monocular Visual Odometry: Photometric Calibration, Motion Bias and Rolling Shutter Effect
Nan Yang, Rui Wang, Xiang Gao +1
Monocular visual odometry (VO) and simultaneous localization and mapping (SLAM) have seen tremendous improvements in accuracy, robustness and efficiency, and have gained increasing…
Measuring the Accuracy of Object Detectors and Trackers
Tobias Bottger, Patrick Follmann, Michael Fauser
The accuracy of object detectors and trackers is most commonly evaluated by the Intersection over Union (IoU) criterion. To date, most approaches are restricted to axis-aligned or…
CNN-SLAM: Real-time dense monocular SLAM with learned depth prediction
Keisuke Tateno, Federico Tombari, Iro Laina +1
Given the recent advances in depth prediction from Convolutional Neural Networks (CNNs), this paper investigates how predicted depth maps from a deep neural network can be deployed…
Tracking the Trackers: An Analysis of the State of the Art in Multiple Object Tracking
Laura Leal-Taixé, Anton Milan, Konrad Schindler +3
Standardized benchmarks are crucial for the majority of computer vision applications. Although leaderboards and ranking tables should not be over-claimed, benchmarks often provide…
Dense Multi-view 3D-reconstruction Without Dense Correspondences
Yvain Quéau, Jean Mélou, Jean-Denis Durou +1
We introduce a variational method for multi-view shape-from-shading under natural illumination. The key idea is to couple PDE-based solutions for single-image based shape-from-shad…
Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems
Tim Meinhardt, Michael Moeller, Caner Hazirbas +1
While variational methods have been among the most powerful tools for solving linear inverse problems in imaging, deep (convolutional) neural networks have recently taken the lead…