Demo Data from SIGIR 2026 / reviewers in the wild / expert
Sebastian Klose
dblp:34/7590
· DBLP profile ↗
5ranked-venue papers
2as first author
0since 2021 · last 2015
0009-0000-0449-4050ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 5 · 2 first-authorSystems, architecture and hardware · 3 · 2 first-authorGraphics, computer vision, multimedia, augmented reality and games · 2
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Artificial intelligence
2 papers |
3D vision · 100% | |
| Computer graphics and multimedia
1 paper |
Image and video processing · 100% |
Topics — the 6 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › 3D vision
3d reconstruction |
0.2 | 1 | 2015 | Variational PatchMatch MultiView Reconstruction and Refinement · ICCV 2015 |
Computer vision › 3D vision › 3d reconstruction
multi-view stereo |
0.2 | 1 | 2015 | Variational PatchMatch MultiView Reconstruction and Refinement · ICCV 2015 |
Image and video processing › stereo vision
dense stereo |
0.2 | 1 | 2015 | Fast dense stereo correspondences by binary locality sensitive hashing · ICRA 2015 |
Image and video processing › stereo vision
stereo matching |
0.2 | 1 | 2015 | Fast dense stereo correspondences by binary locality sensitive hashing · ICRA 2015 |
Computer vision › 3D vision › stereo vision
stereo matching |
0.2 | 1 | 2013 | PM-Huber: PatchMatch with Huber Regularization for Stereo Matching · ICCV 2013 |
Computer vision › 3D vision › stereo vision › stereo matching › disparity refinement
sub-pixel disparity estimation |
0.2 | 1 | 2013 | PM-Huber: PatchMatch with Huber Regularization for Stereo Matching · ICCV 2013 |
Methods — techniques the papers use, named apart from their topics
patchmatch · 0.4variational optimization · 0.2truncated signed distance function · 0.2locality-sensitive hashing · 0.2kernel lifting · 0.2quadratic relaxation · 0.2huber regularization · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | Variational PatchMatch MultiView Reconstruction and RefinementabstractIn this work we propose a novel approach to the problem of multi-view stereo reconstruction. Building upon the previously proposed PatchMatch stereo and PM-Huber algorithm we introduce an extension to the multi-view scenario that employs an iterative refinement scheme. Our proposed approach uses an extended and robustified volumetric truncated signed distance function representation, which is advantageous for the fusion of refined depth maps and also for raycasting the current reconstruction estimation together with estimated depth normals into arbitrary camera views. We formulate the combined multi-view stereo reconstruction and refinement as a variational optimization problem. The newly introduced plane based smoothing term in the energy formulation is guided by the current reconstruction confidence and the image contents. Further we propose an extension of the PatchMatch scheme with an additional KLT step to avoid unnecessary sampling iterations. Improper camera poses are corrected by a direct image aligment step that performs robust outlier compensation by means of a recently proposed kernel lifting framework. To speed up the optimization of the variational formulation an adapted scheme is used for faster convergence. Philipp Heise, Brian Jensen, Sebastian Klose, Alois C. Knoll |
ICCV | 3 |
| 2015 | Fast dense stereo correspondences by binary locality sensitive hashingabstractThe stereo correspondence problem is still a highly active topic of research with many applications in the robotic domain. Still many state of the art algorithms proposed to date are unable to reasonably handle high resolution images due to their run time complexities or memory requirements. In this work we propose a novel stereo correspondence estimation algorithm that employs binary locality sensitive hashing and is well suited to implementation on the GPU. Our proposed method is capable of processing very high-resolution stereo images at near real-time rates. An evaluation on the new Middlebury and Disney high-resolution stereo benchmarks demonstrates that our proposed method performs well compared to existing state of the art algorithms. Philipp Heise, Brian Jensen, Sebastian Klose, Alois C. Knoll |
ICRA | 3 |
| 2013 | PM-Huber: PatchMatch with Huber Regularization for Stereo MatchingabstractMost stereo correspondence algorithms match support windows at integer-valued disparities and assume a constant disparity value within the support window. The recently proposed Patch Match stereo algorithm by Bleyer et al. overcomes this limitation of previous algorithms by directly estimating planes. This work presents a method that integrates the Patch Match stereo algorithm into a variational smoothing formulation using quadratic relaxation. The resulting algorithm allows the explicit regularization of the disparity and normal gradients using the estimated plane parameters. Evaluation of our method in the Middlebury benchmark shows that our method outperforms the traditional integer-valued disparity strategy as well as the original algorithm and its variants in sub-pixel accurate disparity estimation. Philipp Heise, Sebastian Klose, Brian Jensen, Alois C. Knoll |
ICCV | 2 |
| 2013 | Efficient compositional approaches for real-time robust direct visual odometry from RGB-D dataabstractIn this paper we give an evaluation of different methods for computing frame-to-frame motion estimates for a moving RGB-D sensor, by means of aligning two images using photometric error minimization. These kind of algorithms have recently shown to be very accurate and robust and therefore provide an attractive solution for robot ego-motion estimation and navigation. We demonstrate three different alignment strategies, namely the Forward-Compositional, the Inverse-Compositional and the Efficient Second-Order Minimization approach, in a general robust estimation framework. We further show how estimating global affine illumination changes, in general improves the performance of the algorithms. We compare our results with recently published work, considered as state-of-the art in this field, and show that our solutions are in general more precise and can perform in real-time on standard hardware. Sebastian Klose, Philipp Heise, Alois C. Knoll |
IROS | 1 |
| 2010 | Markerless, vision-assisted flight control of a quadrocopterabstractIn this paper, we present a system for controlling a quadrocopter using both optical and inertial measurements. We show how to use external stereo camera measurements for visual servoing, by onboard fusion at high rates, only natural features provided by the vehicle and without any active marker. In our experiments, we show the accuracy and robustness of our system during indoor flights, as well as robustness to external flight disturbances. Sebastian Klose, Michael Achtelik, Giorgio Panin, Florian Holzapfel, Alois C. Knoll |
IROS | 1 |