74 citations · 78 across the 3 of their papers we have counts for
7 papers
LaMAR: Benchmarking Localization and Mapping for Augmented Reality
Paul-Edouard Sarlin, Mihai Dusmanu, Johannes L. Schönberger +5
Localization and mapping is the foundational technology for augmented reality (AR) that enables sharing and persistence of digital content in the real world. While significant prog…
Learning-Based Dimensionality Reduction for Computing Compact and Effective Local Feature Descriptors
Hao Dong, Xieyuanli Chen, Mihai Dusmanu +3
A distinctive representation of image patches in form of features is a key component of many computer vision and robotics tasks, such as image matching, image retrieval, and visual…
DeepVideoMVS: Multi-View Stereo on Video with Recurrent Spatio-Temporal Fusion
Arda Düzçeker, Silvano Galliani, Christoph Vogel +3
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 curr…
Cross-Descriptor Visual Localization and Mapping
Mihai Dusmanu, Ondrej Miksik, Johannes L. Schönberger +1
Visual localization and mapping is the key technology underlying the majority of mixed reality and robotics systems. Most state-of-the-art approaches rely on local features to esta…
Privacy-Preserving Image Features via Adversarial Affine Subspace Embeddings
Mihai Dusmanu, Johannes L. Schönberger, Sudipta N. Sinha +1
Many computer vision systems require users to upload image features to the cloud for processing and storage. These features can be exploited to recover sensitive information about…
Multi-View Optimization of Local Feature Geometry
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. Current approaches to local featur…