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Found 10 papers, 2 papers with code
Privacy Preserving Structure-from-Motion
The recent trend towards cloud-based localization and mapping systems has raised significant privacy concerns.
LaMAR: Benchmarking Localization and Mapping for Augmented Reality
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.
Privacy Preserving Localization and Mapping From Uncalibrated Cameras
In this paper, we propose a solution to the uncalibrated privacy preserving localization and mapping problem.
DeepVideoMVS: Multi-View Stereo on Video with Recurrent Spatio-Temporal Fusion
We propose an online multi-view depth prediction approach on posed video streams, where the scene geometry information computed in the previous time steps is propagated to the current time step in an efficient and geometrically plausible way.
PatchmatchNet: Learned Multi-View Patchmatch Stereo
We present PatchmatchNet, a novel and learnable cascade formulation of Patchmatch for high-resolution multi-view stereo.
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Privacy Preserving Image Queries for Camera Localization
Even if only image features are uploaded, the privacy concerns remain as the images can be reconstructed fairly well from feature locations and descriptors.
Privacy Preserving Image-Based Localization
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.
Consensus Maximization for Semantic Region Correspondences
We propose a novel method for the geometric registration of semantically labeled regions.
Consensus Maximization With Linear Matrix Inequality Constraints
While randomized methods like RANSAC are fast, they do not guarantee global optimality and fail to manage large amounts of outliers.
Turning Mobile Phones into 3D Scanners
In this paper, we propose an efficient and accurate scheme for the integration of multiple stereo-based depth measurements.
