Torsten Sattler

Docent vid Digitala bildsystem och bildanalys

Torsten Sattler är docent i forskargruppen Datorseende och medicinsk bildanalys.

Källa: chalmers.se
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Visar 29 publikationer

2021

InLoc: Indoor Visual Localization with Dense Matching and View Synthesis

Hajime Taira, Masatoshi Okutomi, Torsten Sattler et al
IEEE Transactions on Pattern Analysis and Machine Intelligence. Vol. 43 (4), p. 1293-1307
Artikel i vetenskaplig tidskrift
2021

Are Large-Scale 3D Models Really Necessary for Accurate Visual Localization

Akihiko Torii, Hajime Taira, Josef Sivic et al
IEEE Transactions on Pattern Analysis and Machine Intelligence. Vol. 43 (3), p. 814-829
Artikel i vetenskaplig tidskrift
2020

To Learn or Not to Learn: Visual Localization from Essential Matrices

Qunjie Zhou, Torsten Sattler, Marc Pollefeys et al
Proceedings - IEEE International Conference on Robotics and Automation, p. 3319-3326
Paper i proceeding
2020

Making Affine Correspondences Work in Camera Geometry Computation

Daniel Barath, Michal Polic, Wolfgang Förstner et al
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 12356 LNCS, p. 723-740
Paper i proceeding
2020

Large-scale, real-time visual–inertial localization revisited

Simon Lynen, Bernhard Zeisl, Dror Aiger et al
International Journal of Robotics Research. Vol. 39 (9), p. 1061-1084
Artikel i vetenskaplig tidskrift
2020

Single-Image Depth Prediction Makes Feature Matching Easier

Carl Toft, Daniyar Turmukhambetov, Torsten Sattler et al
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 12361 LNCS, p. 473-492
Paper i proceeding
2020

Long-Term Visual Localization Revisited

Carl Toft, Will Maddern, Akihiko Torii et al
IEEE Transactions on Pattern Analysis and Machine Intelligence. Vol. In press
Artikel i vetenskaplig tidskrift
2020

Using Image Sequences for Long-Term Visual Localization

Erik Stenborg, Torsten Sattler, Lars Hammarstrand
Proceedings - 2020 International Conference on 3D Vision, 3DV 2020, p. 938-948
Paper i proceeding
2020

SurfelMeshing: Online Surfel-Based Mesh Reconstruction

Thomas Schops, Torsten Sattler, Marc Pollefeys
IEEE Transactions on Pattern Analysis and Machine Intelligence. Vol. 42 (10), p. 2494-2507
Artikel i vetenskaplig tidskrift
2020

Infrastructure-Based Multi-camera Calibration Using Radial Projections

Yukai Lin, Viktor Larsson, Marcel Geppert et al
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 12361 LNCS, p. 327-344
Paper i proceeding
2020

Why Having 10,000 Parameters in Your Camera Model Is Better Than Twelve

Thomas Schops, Viktor Larsson, Marc Pollefeys et al
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, p. 2532-2541
Paper i proceeding
2020

Handcrafted Outlier Detection Revisited

Luca Cavalli, Viktor Larsson, Martin Ralf Oswald et al
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 12364 LNCS, p. 770-787
Paper i proceeding
2020

Self-Supervised Linear Motion Deblurring

Peidong Liu, Joel Janai, Marc Pollefeys et al
IEEE Robotics and Automation Letters. Vol. 5 (2), p. 2475-2482
Artikel i vetenskaplig tidskrift
2020

Beyond Controlled Environments: 3D Camera Re-localization in Changing Indoor Scenes

Johanna Wald, Torsten Sattler, Stuart Golodetz et al
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 12352 LNCS, p. 467-487
Paper i proceeding
2020

Deep LiDAR localization using optical flow sensor-map correspondences

Anders Sunegård, Lennart Svensson, Torsten Sattler
Proceedings - 2020 International Conference on 3D Vision, 3DV 2020, p. 838-847
Paper i proceeding
2019

Understanding the Limitations of CNN-based Absolute Camera Pose Regression

Torsten Sattler, Qunjie Zhou, Marc Pollefeys et al
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, p. 3297-3307
Paper i proceeding
2019

IMAGE-TO-IMAGE TRANSLATION for ENHANCED FEATURE MATCHING, IMAGE RETRIEVAL and VISUAL LOCALIZATION

M. S. Mueller, Torsten Sattler, Marc Pollefeys et al
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. 4 (2/W7), p. 111-119
Paper i proceeding
2019

Fine-Grained Segmentation Networks: Self-Supervised Segmentation for Improved Long-Term Visual Localization

Måns Larsson, Erik Stenborg, Carl Toft et al
Proceedings of the IEEE International Conference on Computer Vision (October), p. 31-41
Paper i proceeding
2019

Project AutoVision: Localization and 3D Scene Perception for an Autonomous Vehicle with a Multi-Camera System

Lionel Heng, Benjamin Choi, Zhaopeng Cui et al
2019 INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), p. 4695-4702
Paper i proceeding
2019

Efficient 2D-3D Matching for Multi-Camera Visual Localization

Marcel Geppert, Peidong Liu, Zhaopeng Cui et al
2019 INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), p. 5972-5978
Paper i proceeding
2019

A cross-season correspondence dataset for robust semantic segmentation

Måns Larsson, Erik Stenborg, Lars Hammarstrand et al
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Vol. 2019-June, p. 9524-9534
Paper i proceeding
2019

Is this the right place? geometric-semantic pose verification for indoor visual localization

Hajime Taira, Ignacio Rocco, Jiri Sedlar et al
Proceedings of the IEEE International Conference on Computer Vision. Vol. 2019-October, p. 4372-4382
Paper i proceeding
2019

Night-to-day image translation for retrieval-based localization

Asha Anoosheh, Torsten Sattler, Radu Timofte et al
Proceedings - IEEE International Conference on Robotics and Automation. Vol. 2019-May, p. 5958-5964
Paper i proceeding
2019

Hybrid scene Compression for Visual Localization

Federico Camposeco, Andrea Cohen, Marc Pollefeys et al
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), p. 7645-7654
Paper i proceeding
2019

Bad slam: Bundle adjusted direct RGB-D slam

Thomas Schops, Torsten Sattler, Marc Pollefeys
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Vol. 2019-June, p. 134-144
Paper i proceeding
2019

D2-Net: A Trainable CNN for Joint Description and Detection of Local Features

Mihai Dusmanu, Ignacio Rocco, Tomas Pajdla et al
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), p. 8084-8093
Paper i proceeding
2019

Revisiting Radial Distortion Absolute Pose

Viktor Larsson, Torsten Sattler, Zuzana Kukelova et al
2019 IEEE/CVF International Conference on Computer Vision (ICCV), p. 1062-1071
Paper i proceeding
2019

Incremental visual-inertial 3d mesh generation with structural regularities

Antoni Rosinol, Torsten Sattler, Marc Pollefeys et al
Proceedings - IEEE International Conference on Robotics and Automation. Vol. 2019-May, p. 8220-8226
Paper i proceeding
2019

Real-Time Dense Mapping for Self-Driving Vehicles using Fisheye Cameras

Zhaopeng Cui, Lionel Heng, Ye Chuan Yeo et al
2019 INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), p. 6087-6093
Paper i proceeding

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Visar 3 forskningsprojekt

2020–2024

Understanding and Overcoming the Limitations of Convolutional Neural Networks for Visual Localization (VisLocLearn)

Torsten Sattler Digitala bildsystem och bildanalys
Kunal Chelani Digitala bildsystem och bildanalys
Chalmers AI Research Centre

2019–2021

Datorseende och maskininlärning för robot system

Knut Åkesson Automation
Torsten Sattler Digitala bildsystem och bildanalys
Yiannis Karayiannidis Mekatronik
Chalmers AI-forskningscentrum (CHAIR)

2019–2021

Projekt ViMCoR

Knut Åkesson Automation
Yiannis Karayiannidis Mekatronik
Torsten Sattler Digitala bildsystem och bildanalys
Martin Fabian Automation
Ze Zhang Automation
Sabino Francesco Roselli Automation
Volvo Group

Det kan finnas fler projekt där Torsten Sattler medverkar, men du måste vara inloggad som anställd på Chalmers för att kunna se dem.