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Cross-Descriptor Visual Localization and Mapping
(2021)2021 IEEE/CVF International Conference on Computer Vision (ICCV)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 establish correspondences between images. In this paper, we present three novel scenarios for localization and mapping which require the continuous update of feature representations and the ability to match across different feature types. While localization and ...Conference Paper -
Privacy-Preserving Image Features via Adversarial Affine Subspace Embeddings
(2021)2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)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 the scene or subjects, e.g., by reconstructing the appearance of the original image. To address this privacy concern, we propose a new privacy-preserving feature representation. The core idea of our work is to drop constraints from each feature descriptor by ...Conference Paper -
LaMAR: Benchmarking Localization and Mapping for Augmented Reality
(2022)Lecture Notes in Computer Science ~ Computer Vision – ECCV 2022Localization and mapping is the foundational technology for augmented reality (AR) that enables sharing and persistence of digital content in the real world. While significant progress has been made, researchers are still mostly driven by unrealistic benchmarks not representative of real-world AR scenarios. In particular, benchmarks are often based on small-scale datasets with low scene diversity, captured from stationary cameras, and ...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