• Publications
  • Influence
A benchmark for the evaluation of RGB-D SLAM systems
TLDR
A large set of image sequences from a Microsoft Kinect with highly accurate and time-synchronized ground truth camera poses from a motion capture system is recorded for the evaluation of RGB-D SLAM systems. Expand
FlowNet: Learning Optical Flow with Convolutional Networks
TLDR
This paper constructs CNNs which are capable of solving the optical flow estimation problem as a supervised learning task, and proposes and compares two architectures: a generic architecture and another one including a layer that correlates feature vectors at different image locations. Expand
LSD-SLAM: Large-Scale Direct Monocular SLAM
TLDR
A novel direct tracking method which operates on \(\mathfrak{sim}(3)\), thereby explicitly detecting scale-drift, and an elegant probabilistic solution to include the effect of noisy depth values into tracking are introduced. Expand
A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation
  • N. Mayer, Eddy Ilg, +4 authors T. Brox
  • Computer Science, Mathematics
  • IEEE Conference on Computer Vision and Pattern…
  • 7 December 2015
TLDR
This paper proposes three synthetic stereo video datasets with sufficient realism, variation, and size to successfully train large networks and presents a convolutional network for real-time disparity estimation that provides state-of-the-art results. Expand
Direct Sparse Odometry
TLDR
The experiments show that the presented approach significantly outperforms state-of-the-art direct and indirect methods in a variety of real-world settings, both in terms of tracking accuracy and robustness. Expand
One-Shot Video Object Segmentation
TLDR
One-Shot Video Object Segmentation (OSVOS), based on a fully-convolutional neural network architecture that is able to successively transfer generic semantic information, learned on ImageNet, to the task of foreground segmentation, and finally to learning the appearance of a single annotated object of the test sequence (hence one-shot). Expand
The wave kernel signature: A quantum mechanical approach to shape analysis
TLDR
Both theoretically and in quantitative experiments it is demonstrated that the WKS is substantially more discriminative and therefore allows for better feature matching than the commonly used Heat Kernel Signature. Expand
Dense visual SLAM for RGB-D cameras
TLDR
This paper proposes a dense visual SLAM method for RGB-D cameras that minimizes both the photometric and the depth error over all pixels, and proposes an entropy-based similarity measure for keyframe selection and loop closure detection. Expand
An evaluation of the RGB-D SLAM system
We present an approach to simultaneous localization and mapping (SLAM) for RGB-D cameras like the Microsoft Kinect. Our system concurrently estimates the trajectory of a hand-held Kinect andExpand
Robust odometry estimation for RGB-D cameras
TLDR
This work registers two consecutive RGB-D frames directly upon each other by minimizing the photometric error using non-linear minimization in combination with a coarse-to-fine scheme, and proposes to use a robust error function that reduces the influence of large residuals. Expand
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