Search Results for author: Johannes L. Schönberger

Found 15 papers, 6 papers with code

ALSTER: A Local Spatio-Temporal Expert for Online 3D Semantic Reconstruction

no code implementations29 Nov 2023 Silvan Weder, Francis Engelmann, Johannes L. Schönberger, Akihito Seki, Marc Pollefeys, Martin R. Oswald

Using these main contributions, our method can enable scenarios with real-time constraints and can scale to arbitrary scene sizes by processing and updating the scene only in a local region defined by the new measurement.

3D Semantic Segmentation Mixed Reality

Privacy Preserving Localization via Coordinate Permutations

no code implementations ICCV 2023 Linfei Pan, Johannes L. Schönberger, Viktor Larsson, Marc Pollefeys

Recent methods on privacy-preserving image-based localization use a random line parameterization to protect the privacy of query images and database maps.

Image-Based Localization Pose Estimation +1

LaMAR: Benchmarking Localization and Mapping for Augmented Reality

no code implementations19 Oct 2022 Paul-Edouard Sarlin, Mihai Dusmanu, Johannes L. Schönberger, Pablo Speciale, Lukas Gruber, Viktor Larsson, Ondrej Miksik, Marc Pollefeys

To close this gap, we introduce LaMAR, a new benchmark with a comprehensive capture and GT pipeline that co-registers realistic trajectories and sensor streams captured by heterogeneous AR devices in large, unconstrained scenes.

Benchmarking

Reconstructing and grounding narrated instructional videos in 3D

no code implementations9 Sep 2021 Dimitri Zhukov, Ignacio Rocco, Ivan Laptev, Josef Sivic, Johannes L. Schönberger, Bugra Tekin, Marc Pollefeys

Contrary to the standard scenario of instance-level 3D reconstruction, where identical objects or scenes are present in all views, objects in different instructional videos may have large appearance variations given varying conditions and versions of the same product.

3D Reconstruction

Cross-Descriptor Visual Localization and Mapping

1 code implementation ICCV 2021 Mihai Dusmanu, Ondrej Miksik, Johannes L. Schönberger, Marc Pollefeys

Visual localization and mapping is the key technology underlying the majority of mixed reality and robotics systems.

Mixed Reality Visual Localization

NeuralFusion: Online Depth Fusion in Latent Space

1 code implementation CVPR 2021 Silvan Weder, Johannes L. Schönberger, Marc Pollefeys, Martin R. Oswald

We present a novel online depth map fusion approach that learns depth map aggregation in a latent feature space.

HoloLens 2 Research Mode as a Tool for Computer Vision Research

1 code implementation25 Aug 2020 Dorin Ungureanu, Federica Bogo, Silvano Galliani, Pooja Sama, Xin Duan, Casey Meekhof, Jan Stühmer, Thomas J. Cashman, Bugra Tekin, Johannes L. Schönberger, Pawel Olszta, Marc Pollefeys

Mixed reality headsets, such as the Microsoft HoloLens 2, are powerful sensing devices with integrated compute capabilities, which makes it an ideal platform for computer vision research.

Mixed Reality

Multi-View Optimization of Local Feature Geometry

1 code implementation ECCV 2020 Mihai Dusmanu, Johannes L. Schönberger, Marc Pollefeys

In this work, we address the problem of refining the geometry of local image features from multiple views without known scene or camera geometry.

Camera Localization

Privacy Preserving Image-Based Localization

no code implementations CVPR 2019 Pablo Speciale, Johannes L. Schönberger, Sing Bing Kang, Sudipta N. Sinha, Marc Pollefeys

Current localization systems rely on the persistent storage of 3D point clouds of the scene to enable camera pose estimation, but such data reveals potentially sensitive scene information.

Image-Based Localization Mixed Reality +2

Semantic Visual Localization

no code implementations CVPR 2018 Johannes L. Schönberger, Marc Pollefeys, Andreas Geiger, Torsten Sattler

Robust visual localization under a wide range of viewing conditions is a fundamental problem in computer vision.

Visual Localization

scikit-image: Image processing in Python

1 code implementation23 Jul 2014 Stefan van der Walt, Johannes L. Schönberger, Juan Nunez-Iglesias, François Boulogne, Joshua D. Warner, Neil Yager, Emmanuelle Gouillart, Tony Yu, the scikit-image contributors

scikit-image is an image processing library that implements algorithms and utilities for use in research, education and industry applications.

2D Object Detection

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