Efficient and accurate bird sound classification is of important for eco...
Deep learning based localization and mapping approaches have recently em...
Artificial intelligence onboard satellites has the potential to reduce d...
A truly generalizable approach to rigid segmentation and motion estimati...
To date, the majority of positioning systems have been designed to opera...
Indoor positioning systems have received a lot of attention recently due...
Deep learning has led to great progress in the detection of mobile (i.e....
Self-supervised deep learning methods for joint depth and ego-motion
est...
Sampling is a key operation in point-cloud task and acts to increase
com...
Scene flow is a powerful tool for capturing the motion field of 3D point...
Unmanned aerial vehicles (UAVs) have been used for many applications in
...
Ubiquitous positioning for pedestrian in adverse environment has served ...
Camera localization is a fundamental and crucial problem for many roboti...
Direction finding and positioning systems based on RF signals are
signif...
mmWave FMCW radar has attracted huge amount of research interest for
hum...
Recently, physics-informed neural networks (PINNs) have offered a powerf...
We present a new framework SoundDet, which is an end-to-end trainable an...
Simultaneous Localization and Mapping (SLAM) system typically employ
vis...
Accurately describing and detecting 2D and 3D keypoints is crucial to
es...
Extracting robust and general 3D local features is key to downstream tas...
Accurate motion capture of aerial robots in 3-D is a key enabler for
aut...
Positional estimation is of great importance in the public safety sector...
An essential prerequisite for unleashing the potential of supervised dee...
Deep learning based localization and mapping has recently attracted
sign...
Recent learning-based research has achieved impressive results in the fi...
In this paper, we present a novel end-to-end learning-based LiDAR
reloca...
Modern inertial measurements units (IMUs) are small, cheap, energy effic...
Autonomous vehicles and mobile robotic systems are typically equipped wi...
Demand for smartwatches has taken off in recent years with new models wh...
We study the problem of efficient semantic segmentation for large-scale ...
In the last decade, numerous supervised deep learning approaches requiri...
Calibration of the zero-velocity detection threshold is an essential
pre...
We introduce a recent symplectic integration scheme derived for solving
...
Odometry is of key importance for localization in the absence of a map. ...
Magneto-inductive navigation is an inexpensive and easily deployable sol...
Visual odometry shows excellent performance in a wide range of environme...
With the fast-growing demand of location-based services in various indoo...
Deep learning has achieved impressive results in camera localization, bu...
Facial recognition is a key enabling component for emerging Internet of
...
Dynamical models estimate and predict the temporal evolution of physical...
This paper presents a novel method to distill knowledge from a deep pose...
We propose a novel, conceptually simple and general framework for instan...
Inspired by the cognitive process of humans and animals, Curriculum Lear...
A Bayesian zero-velocity detector for foot-mounted inertial navigation
s...
Deep learning approaches for Visual-Inertial Odometry (VIO) have proven
...
Deep Reinforcement Learning (DRL) has been applied successfully to many
...
Due to the sparse rewards and high degree of environment variation,
rein...
Inertial information processing plays a pivotal role in ego-motion aware...
Advances in micro-electro-mechanical (MEMS) techniques enable inertial
m...
In the last decade, supervised deep learning approaches have been extens...