Graph neural networks (GNNs) are effective machine learning models for m...
Heterogeneous Information Networks (HINs) are information networks with
...
Online unsupervised video object segmentation (UVOS) uses the previous f...
Monocular depth estimation plays a fundamental role in computer vision. ...
This work aims to estimate a high-quality depth map from a single RGB im...
This paper investigates the problem of sampling and reconstructing bandp...
Local feature provides compact and invariant image representation for va...
Unsupervised monocular trained depth estimation models make use of adjac...
Unsupervised video object segmentation (UVOS) aims at automatically
sepa...
Space-time adaptive processing (STAP) is one of the most effective appro...
Aircraft detection in Synthetic Aperture Radar (SAR) imagery is a challe...
The generative adversarial network (GAN) is successfully applied to stud...
On-policy deep reinforcement learning algorithms have low data utilizati...
Depth estimation is getting a widespread popularity in the computer visi...
Features play an important role in various visual tasks, especially in v...
Facial MicroExpressions (MEs) are spontaneous, involuntary facial moveme...
Betweenness centrality (BC) is one of the most used centrality measures ...
Recent breakthroughs in Go play and strategic games have witnessed the g...
Radar interferometry usually exploits two complex-valued radar images wi...
This paper presents a quadrature compressive sampling (QuadCS) and assoc...