We propose Neural Gradient Learning (NGL), a deep learning approach to l...
To improve the data rate in differential chaos shift keying (DCSK) based...
Despite the rapid progress in self-supervised learning (SSL), end-to-end...
Dense retrieval (DR) converts queries and documents into dense embedding...
We propose a novel method called SHS-Net for oriented normal estimation ...
This paper investigates the bit-interleaved coded generalized spatial
mo...
We propose a novel normal estimation method called HSurf-Net, which can
...
Surface reconstruction for point clouds is an important task in 3D compu...
Deep learning has made great strides for object detection in images. The...
This paper proposes a high-throughput short reference differential chaos...
People with blindness and low vision (pBLV) experience significant chall...
To achieve reliable and efficient transmissions in free-space optical (F...
Sketch-based 3D shape retrieval (SBSR) is an important yet challenging t...
Omnidirectional images and videos can provide immersive experience of
re...
In this paper, we propose a reconfigurable intelligent surface (RIS)-ass...
CT organ segmentation on computed tomography (CT) images becomes a
signi...
Learning representations for point clouds is an important task in 3D com...
Professional news media organizations have always touted the importance ...
Network embedding is an effective technique to learn the low-dimensional...
Product ranking is a crucial component for many e-commerce services. One...
Structure information extraction refers to the task of extracting struct...
Advanced wearable devices are increasingly incorporating high-resolution...
As an established bandwidth-efficient coded modulation technique,
bit-in...
The neural machine translation model assumes that syntax knowledge can b...
Learning robust 3D shape segmentation functions with deep neural network...
Though deep learning methods have shown great success in 3D point cloud ...
This paper concerns the research problem of point cloud registration to ...
With the popularity of 3D sensors in self-driving and other robotics
app...
Lane segmentation is a challenging issue in autonomous driving system
de...
The conventional LoRa system is not able to sustain long-range communica...
Analyzing the structure of proteins is a key part of understanding their...
Non-linear (large) time warping is a challenging source of nuisance in
t...
In this work, we develop a pair of rate-diverse encoder and decoder for ...
For short distance traveling in crowded urban areas, bike share services...
We present a new technique named "Meta Deformation Network" for 3D shape...
Adaptive link selection for buffer-aided relaying can achieve significan...
Code index modulated multi-carrier M-ary differential chaos shift keying...
As a typical example of bandwidth-efficient techniques, bit-interleaved ...
To better address challenging issues of the irregularity and inhomogenei...
Learning to predict scene depth and camera motion from RGB inputs only i...
Monocular depth estimation is a challenging task that aims to predict a
...
Environment perception, including object detection and distance estimati...
Given new pairs of source and target point sets, standard point set
regi...
This paper focuses on robotic picking tasks in cluttered scenario. Becau...
Point set registration is defined as a process to determine the spatial
...
Block-fading (BF) channel, also known as slow-fading channel, is a type ...
Internet of Things (IoT) have motivated a paradigm shift in the developm...
Due to the large cross-modality discrepancy between 2D sketches and 3D
s...
Recommendation systems play a vital role to keep users engaged with
pers...
This paper proposes a novel constraint-handling mechanism named angle-ba...