Either RGB images or inertial signals have been used for the task of mot...
SAR images are highly sensitive to observation configurations, and they
...
Currently, density-based clustering algorithms are widely applied becaus...
For invasive breast cancer, immunohistochemical (IHC) techniques are oft...
Human and environment sensing are two important topics in Computer Visio...
Modeling non-Lambertian effects such as facial specularity leads to a mo...
Imitation learning aims to mimic the behavior of experts without explici...
Gallium-based liquid metal is getting increased attention in conformal
f...
Neural radiance fields (NeRF) achieve highly photo-realistic novel-view
...
By supervising camera rays between a scene and multi-view image planes, ...
Deep neural networks (DNNs), are widely used in many industries such as ...
Achieving highly accurate kinematic or simulator models that are close t...
Backdoor attacks have been shown to be a serious security threat against...
Morphable models are essential for the statistical modeling of 3D faces....
Convex model predictive controls (MPCs) with a single rigid body model h...
Spiking neural networks (SNNs) are brain-inspired machine learning algor...
Although significant progress has been made to audio-driven talking face...
Forward modeling of wave scattering and radar imaging mechanisms is the ...
The evaluation of human epidermal growth factor receptor 2 (HER2) expres...
Graph neural networks (GNNs) have been widely used in many real applicat...
In portraits, eyeglasses may occlude facial regions and generate cast sh...
Motion capture from sparse inertial sensors has shown great potential
co...
RGBD-based real-time dynamic 3D reconstruction suffers from inaccurate
i...
Objectives: To develop and validate a deep learning (DL)-based primary t...
Backdoor attacks have been shown to be a serious threat against deep lea...
A general adaptive refinement strategy for solving linear elliptic parti...
Experience replay is widely used in various deep off-policy reinforcemen...
Motion capture is facing some new possibilities brought by the inertial
...
Despite previous success in generating audio-driven talking heads, most ...
We address the problem of tensor decomposition in application to
directi...
We present the first method for real-time full body capture that estimat...
In order to improve the accuracy and resolution for transmit beamspace
m...
We develop a new tensor model for slow-time multiple-input multiple outp...
Deep learning in remote sensing has become an international hype, but it...
We present a novel method for monocular hand shape and pose estimation a...
Recent advances in deep reinforcement learning (RL) have demonstrated it...
Bas-relief generation based on 3d models is a hot topic in computer grap...
In this paper, we investigate a novel problem of telling the difference
...
Ridge-valley features are important elements of point clouds, as they co...
Universal style transfer tries to explicitly minimize the losses in feat...
We propose a real-time DNN-based technique to segment hand and object of...
Despite the advantages of all-weather and all-day high-resolution imagin...
Despite the advantages of all-weather and all-day high-resolution imagin...
Camera motion estimation is a key technique for 3D scene reconstruction ...
In recent years, the satellite videos have been captured by a moving
sat...
Researches in novel viewpoint synthesis majorly focus on interpolation f...
Standing at the paradigm shift towards data-intensive science, machine
l...
A deep neural networks based method is proposed to convert single
polari...
Community Question Answering (CQA) websites have become valuable reposit...
Trust is a fundamental concept in many real-world applications such as
e...