Loop closing and relocalization are crucial techniques to establish reli...
In this paper, we draw inspiration from Alberto Elfes' pioneering work i...
How to generate diverse, life-like, and unlimited long head/body sequenc...
Discriminating the traversability of terrains is a crucial task for
auto...
For autonomous driving, traversability analysis is one of the most basic...
In this paper, we propose the first fully push-forward-based Distributio...
Multi-camera 3D perception has emerged as a prominent research field in
...
Point cloud registration is an important task in robotics and autonomous...
Data augmentation has been widely used to improve generalization in trai...
In this paper, the wireless hierarchical federated learning (HFL) is
rev...
Freespace detection is an essential component of autonomous driving
tech...
Mask-based pre-training has achieved great success for self-supervised
l...
Self-supervised learning (SSL) has achieved great success in a variety o...
State-of-the-art autonomous driving systems rely on high definition (HD)...
Deep learning has recently demonstrated its promising performance for
vi...
The recent, counter-intuitive discovery that deep generative models (DGM...
The feedback capacities of the Gaussian multiple-access channel (GMAC) a...
3D moving object detection is one of the most critical tasks in dynamic ...
In narrow asymptotic settings Gaussian VAE models of continuous data hav...
LIDAR is one of the most important sensors for Unmanned Ground Vehicles
...
Although variational autoencoders (VAEs) represent a widely influential ...
Recently, the physical layer security (PLS) of the communication systems...
Neural networks can be compressed to reduce memory and computational
req...
Secure and reliable transmission over communication channels is first
ch...
In this paper, density evolution-based construction methods to design go...
Selecting attractive photos from a human action shot sequence is quite
c...