Search
Results
-
A Vote-and-Verify Strategy for Fast Spatial Verification in Image Retrieval
(2017)Lecture Notes in Computer Science ~ 13th Asian Conference on Computer Vision, Taipei, Taiwan, November 20-24, 2016, Revised Selected Papers. Part IConference Paper -
VSO: Visual Semantic Odometry
(2018)Lecture Notes in Computer Science ~ Computer Vision – ECCV 2018Conference Paper -
Mapping on the Fly: Real-Time 3D Dense Reconstruction, Digital Surface Map and Incremental Orthomosaic Generation for Unmanned Aerial Vehicles
(2017)Springer Proceedings in Advanced Robotics ~ Field and Service Robotics: Results of the 11th International ConferenceConference Paper -
Learning Priors for Semantic 3D Reconstruction
(2018)Lecture Notes in Computer Science ~ Computer Vision – ECCV 2018Conference Paper -
Learning to Fuse Proposals from Multiple Scanline Optimizations in Semi-Global Matching
(2018)Lecture Notes in Computer Science ~ Computer Vision – ECCV 2018: 15th European Conference, Munich, Germany, September 8-14, 2018, Proceedings, Part XIIIConference Paper -
Comparative Evaluation of Hand-Crafted and Learned Local Features
(2017)2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)Conference Paper -
A Multi-View Stereo Benchmark with High-Resolution Images and Multi-Camera Videos
(2017)2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)Conference Paper -
Privacy Preserving Structure-from-Motion
(2020)Lecture Notes in Computer Science ~ Computer Vision – ECCV 2020Over the last years, visual localization and mapping solutions have been adopted by an increasing number of mixed reality and robotics systems. The recent trend towards cloud-based localization and mapping systems has raised significant privacy concerns. These are mainly grounded by the fact that these services require users to upload visual data to their servers, which can reveal potentially confidential information, even if only derived ...Conference Paper -
Multi-view Optimization of Local Feature Geometry
(2020)Lecture Notes in Computer Science ~ Computer Vision – ECCV 2020In this work, we address the problem of refining the geometry of local image features from multiple views without known scene or camera geometry. Current approaches to local feature detection are inherently limited in their keypoint localization accuracy because they only operate on a single view. This limitation has a negative impact on downstream tasks such as Structure-from-Motion, where inaccurate keypoints lead to large errors in ...Conference Paper -
RoutedFusion: Learning Real-Time Depth Map Fusion
(2020)2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)The efficient fusion of depth maps is a key part of most state-of-the-art 3D reconstruction methods. Besides requiring high accuracy, these depth fusion methods need to be scalable and real-time capable. To this end, we present a novel real-time capable machine learning-based method for depth map fusion. Similar to the seminal depth map fusion approach by Curless and Levoy, we only update a local group of voxels to ensure real-time ...Conference Paper