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Found 7 papers, 0 papers with code
Project Aria: A New Tool for Egocentric Multi-Modal AI Research
Egocentric, multi-modal data as available on future augmented reality (AR) devices provides unique challenges and opportunities for machine perception.
NinjaDesc: Content-Concealing Visual Descriptors via Adversarial Learning
We let a feature encoding network and image reconstruction network compete with each other, such that the feature encoder tries to impede the image reconstruction with its generated descriptors, while the reconstructor tries to recover the input image from the descriptors.
Analysis and Mitigations of Reverse Engineering Attacks on Local Feature Descriptors
This poses a potential risk to user privacy.
Domain Adaptation of Learned Features for Visual Localization
We tackle the problem of visual localization under changing conditions, such as time of day, weather, and seasons.
Hierarchy of Alternating Specialists for Scene Recognition
We also introduce a mini-batch soft k-means that allows end-to-end fine-tuning, as well as a novel routing function for assigning images to specialists.
Learned Contextual Feature Reweighting for Image Geo-Localization
We address the problem of large scale image geo-localization where the location of an image is estimated by identifying geo-tagged reference images depicting the same place.
Predicting Good Features for Image Geo-Localization Using Per-Bundle VLAD
We address the problem of recognizing a place depicted in a query image by using a large database of geo-tagged images at a city-scale.
