Visual affordance segmentation identifies the surfaces of an object an a...
Estimating the 6D pose and size of household containers is challenging d...
People may be unaware of the privacy risks of uploading an image online....
Body-worn first-person vision (FPV) camera enables to extract a rich sou...
We propose a decentralised view-overlap recognition framework that opera...
The appearance of objects in underwater images is degraded by the select...
Our voice encodes a uniquely identifiable pattern which can be used to i...
Adversarial attacks modify images with perturbations that change the
pre...
We address the problem of distribution shifts in test-time data with a
p...
Deep neural networks are increasingly deployed for scene analytics, incl...
Humans express their emotions via facial expressions, voice intonation a...
Active Position Estimation (APE) is the task of localizing one or more
t...
The control of a robot for manipulation tasks generally relies on object...
Acoustic and visual sensing can support the contactless estimation of th...
Safe human-to-robot handovers of unknown objects require accurate estima...
Besides its linguistic content, our speech is rich in biometric informat...
Food containers, drinking glasses and cups handled by a person generate
...
We investigate the problem of classifying - from a single image - the le...
Microphone array techniques can improve the acoustic sensing performance...
Underwater images are degraded by the selective attenuation of light tha...
Speaker identification models are vulnerable to carefully designed
adver...
Multi-modal learning relates information across observation modalities o...
Estimating the number of people exposed to digital signage is important ...
We present the first adversarial framework that crafts perturbations tha...
Current deep neural architectures for processing sensor data are mainly
...
Adversarial perturbations can be added to images to protect their conten...
Autonomous Vehicles rely on accurate and robust sensor observations for
...
We present DarkneTZ, a framework that uses an edge device's Trusted Exec...
Machine Learning as a Service (MLaaS) operators provide model training a...
The 3D localisation of an object and the estimation of its properties, s...
Adversarial attacks that generate small L_p-norm perturbations to mislea...
Sensitive inferences and user re-identification are major threats to pri...
Adversarial examples are intentionally perturbed images that mislead
cla...
An effective person re-identification (re-ID) model should learn feature...
Pre-trained Deep Neural Network (DNN) models are increasingly used in
sm...
As an instance-level recognition problem, person re-identification (ReID...
This document describes our submission to the 2018 LOCalization And TrAc...
Cameras mounted on Micro Aerial Vehicles (MAVs) are increasingly used fo...
Data from motion sensors such as accelerometers and gyroscopes embedded ...
Most existing video summarisation methods are based on either supervised...
This paper focuses on multi-sensor anomaly detection for moving cognitiv...
There is growing concern about how personal data are used when users gra...
We propose a cloud-based filter trained to block third parties from uplo...