Search Results for author: Jörg Stückler

Found 15 papers, 5 papers with code

Learning to Adapt Multi-View Stereo by Self-Supervision

no code implementations28 Sep 2020 Arijit Mallick, Jörg Stückler, Hendrik Lensch

We use model-agnostic meta-learning (MAML) to train base parameters which, in turn, are adapted for multi-view stereo on new domains through self-supervised training.

3D Scene Reconstruction Meta-Learning

Planning from Images with Deep Latent Gaussian Process Dynamics

1 code implementation7 May 2020 Nathanael Bosch, Jan Achterhold, Laura Leal-Taixé, Jörg Stückler

We propose to learn a deep latent Gaussian process dynamics (DLGPD) model that learns low-dimensional system dynamics from environment interactions with visual observations.

Gaussian Processes Transfer Learning

SAMP: Shape and Motion Priors for 4D Vehicle Reconstruction

1 code implementation2 May 2020 Francis Engelmann, Jörg Stückler, Bastian Leibe

In this paper, we propose to use 3D shape and motion priors to regularize the estimation of the trajectory and the shape of vehicles in sequences of stereo images.

Platform Pose Estimation

EM-Fusion: Dynamic Object-Level SLAM with Probabilistic Data Association

1 code implementation ICCV 2019 Michael Strecke, Jörg Stückler

The majority of approaches for acquiring dense 3D environment maps with RGB-D cameras assumes static environments or rejects moving objects as outliers.

Multi-Object Tracking Occlusion Handling

Visual-Inertial Mapping with Non-Linear Factor Recovery

9 code implementations13 Apr 2019 Vladyslav Usenko, Nikolaus Demmel, David Schubert, Jörg Stückler, Daniel Cremers

We reconstruct a set of non-linear factors that make an optimal approximation of the information on the trajectory accumulated by VIO.

Motion Estimation

Detailed Dense Inference with Convolutional Neural Networks via Discrete Wavelet Transform

no code implementations6 Aug 2018 Lingni Ma, Jörg Stückler, Tao Wu, Daniel Cremers

Dense pixelwise prediction such as semantic segmentation is an up-to-date challenge for deep convolutional neural networks (CNNs).

Semantic Segmentation

Direct Sparse Odometry with Rolling Shutter

no code implementations ECCV 2018 David Schubert, Nikolaus Demmel, Vladyslav Usenko, Jörg Stückler, Daniel Cremers

Neglecting the effects of rolling-shutter cameras for visual odometry (VO) severely degrades accuracy and robustness.

Visual Odometry

The TUM VI Benchmark for Evaluating Visual-Inertial Odometry

6 code implementations17 Apr 2018 David Schubert, Thore Goll, Nikolaus Demmel, Vladyslav Usenko, Jörg Stückler, Daniel Cremers

For trajectory evaluation, we also provide accurate pose ground truth from a motion capture system at high frequency (120 Hz) at the start and end of the sequences which we accurately aligned with the camera and IMU measurements.

Motion Capture Visual Odometry

Multi-View Deep Learning for Consistent Semantic Mapping with RGB-D Cameras

no code implementations26 Mar 2017 Lingni Ma, Jörg Stückler, Christian Kerl, Daniel Cremers

At test time, the semantics predictions of our network can be fused more consistently in semantic keyframe maps than predictions of a network trained on individual views.

Scene Understanding Semantic Segmentation

Keyframe-Based Visual-Inertial Online SLAM with Relocalization

no code implementations7 Feb 2017 Anton Kasyanov, Francis Engelmann, Jörg Stückler, Bastian Leibe

Our visual-inertial SLAM system is based on a real-time capable visual-inertial odometry method that provides locally consistent trajectory and map estimates.

Pose Tracking Simultaneous Localization and Mapping

Cannot find the paper you are looking for? You can Submit a new open access paper.