Torsten Sattler
Torsten Sattler is an associate professor in the research group Computer vision and medical image analysis. His main research interests focus around developing robust and reliable 3D computer vision algorithms for applications such as Mixed Reality, Self-Driving Cars, and Robotics. To this end, Torsten works on integrating higher-level scene understanding into techniques such as visual localization and mapping. He is further interested in real-time computer vision algorithms and machine learning for computer vision tasks.
Showing 18 publications
To Learn or Not to Learn: Visual Localization from Essential Matrices
Large-scale, real-time visual–inertial localization revisited
SurfelMeshing: Online Surfel-Based Mesh Reconstruction
Self-Supervised Linear Motion Deblurring
IMAGE-TO-IMAGE TRANSLATION for ENHANCED FEATURE MATCHING, IMAGE RETRIEVAL and VISUAL LOCALIZATION
Understanding the Limitations of CNN-based Absolute Camera Pose Regression
Efficient 2D-3D Matching for Multi-Camera Visual Localization
A cross-season correspondence dataset for robust semantic segmentation
Is this the right place? geometric-semantic pose verification for indoor visual localization
Night-to-day image translation for retrieval-based localization
Hybrid scene Compression for Visual Localization
Bad slam: Bundle adjusted direct RGB-D slam
Revisiting Radial Distortion Absolute Pose
Incremental visual-inertial 3d mesh generation with structural regularities
Real-Time Dense Mapping for Self-Driving Vehicles using Fisheye Cameras
D2-Net: A Trainable CNN for Joint Description and Detection of Local Features
Download publication list
You can download this list to your computer.
Filter and download publication list
As logged in user (Chalmers employee) you find more export functions in MyResearch.
You may also import these directly to Zotero or Mendeley by using a browser plugin. These are found herer:
Showing 2 research projects
Vision and machine learning for collaborative robotics