Key. net: Keypoint detection by handcrafted and learned cnn filters revisited
A Barroso-Laguna, K Mikolajczyk - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
We introduce a novel approach for keypoint detection that combines handcrafted and
learned CNN filters within a shallow multi-scale architecture. Handcrafted filters provide …
learned CNN filters within a shallow multi-scale architecture. Handcrafted filters provide …
Segloc: Learning segmentation-based representations for privacy-preserving visual localization
M Pietrantoni, M Humenberger… - Proceedings of the …, 2023 - openaccess.thecvf.com
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 …
leverage robust image segmentation in the context of privacy-preserving visual localization …
Ninjadesc: Content-concealing visual descriptors via adversarial learning
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 …
descriptors, we develop descriptors that conceal the input image content. In particular, we …
Privacy-preserving representations are not enough: Recovering scene content from camera poses
Visual localization is the task of estimating the camera pose from which a given image was
taken and is central to several 3D computer vision applications. With the rapid growth in the …
taken and is central to several 3D computer vision applications. With the rapid growth in the …
Ps-fedgan: An efficient federated learning framework based on partially shared generative adversarial networks for data privacy
Federated Learning (FL) has emerged as an effective learning paradigm for distributed
computation owing to its strong potential in capturing underlying data statistics while …
computation owing to its strong potential in capturing underlying data statistics while …
UFed-GAN: A Secure Federated Learning Framework with Constrained Computation and Unlabeled Data
To satisfy the broad applications and insatiable hunger for deploying low latency multimedia
data classification and data privacy in a cloud-based setting, federated learning (FL) has …
data classification and data privacy in a cloud-based setting, federated learning (FL) has …
PS-FedGAN: An Efficient Federated Learning Framework with Strong Data Privacy
Federated Learning (FL) has emerged as an effective paradigm for distributed learning
systems owing to its strong potential in exploiting underlying data characteristics while …
systems owing to its strong potential in exploiting underlying data characteristics while …
Verifiable access control for augmented reality localization and mapping
Localization and mapping is a key technology for bridging the virtual and physical worlds in
augmented reality (AR). Localization and mapping works by creating and querying maps …
augmented reality (AR). Localization and mapping works by creating and querying maps …
Obfuscation Based Privacy Preserving Representations are Recoverable Using Neighborhood Information
Rapid growth in the popularity of AR/VR/MR applications and cloud-based visual
localization systems has given rise to an increased focus on the privacy of user content in …
localization systems has given rise to an increased focus on the privacy of user content in …
UFed-GAN: Secure Federated Learning over Wireless Sensor Networks with Unlabeled Data
The rising demand for deploying low-latency data analysis and protecting privacy in a cloud-
based setting has led to the emergence of federated learning (FL) as an important learning …
based setting has led to the emergence of federated learning (FL) as an important learning …