Background Data science offers an unparalleled opportunity to identify new insights into
many aspects of human life with recent advances in health care. Using data science in …

Humans can orient themselves in their 3D environments using simple 2D maps. Differently,
algorithms for visual localization mostly rely on complex 3D point clouds that are expensive …

Modern computer vision services often require users to share raw feature descriptors with an
untrusted server. This presents an inherent privacy risk, as raw descriptors may be used to …

Inspired by properties of semantic segmentation, in this paper we investigate how to
leverage robust image segmentation in the context of privacy-preserving visual localization …

We propose to construct a view graph to excavate the information of the whole given
sequence for absolute camera pose estimation. Specifically, we harness GNNs to model the …

Modern camera localization methods that use image retrieval, feature matching, and 3D
structure-based pose estimation require long-term storage of numerous scene images or a …

Lifelong learning aims to train a highly expressive model for a new task while retaining all
knowledge for previous tasks. However, many practical scenarios do not always require the …

In the light of recent analyses on privacy-concerning scene revelation from visual
descriptors, we develop descriptors that conceal the input image content. In particular, we …

With rising demand for indoor location-based services (LBS) such as location-based
marketing, mobile navigation, etc., there has been considerable interest in indoor …

Recent methods on privacy-preserving image-based localization use a random line
parameterization to protect the privacy of query images and database maps. The lifting of …