Although Convolutional Neural Networks (CNNs) have achieved promising re...
Distribution learning focuses on learning the probability density functi...
Recently, images are considered samples from a high-dimensional distribu...
We propose a novel method to learn intractable distributions from their
...
Universal moving object segmentation aims to provide a general model for...
Convolutional neural networks have demonstrated impressive results in ma...
We propose a method SPGNet for 3D human pose estimation that mixes
multi...
In recent years, motion capture technology using computers has developed...
We propose a new Arithmetic Distribution Neural Network (ADNN) for learn...
Objective visual quality assessment of 3D models is a fundamental issue ...
A 3D thinning algorithm erodes a 3D binary image layer by layer to extra...
Brain tumor segmentation from Magnetic Resonance Images (MRIs) is an
imp...
White Matter Injury (WMI) is the most prevalent brain injury in the pret...
We present a new mathematical formulation to estimate the intrinsic
para...
Parkinson's Disease (PD) is one of the most common types of neurological...
Intravascular Ultrasound (IVUS) is an intra-operative imaging modality t...
We introduce new linear mathematical formulations to calculate the focal...
IntraVascular UltraSound (IVUS) is one of the most effective imaging
mod...
Laparoscopic Surgery (LS) is a modern surgical technique whereby the sur...
Image Quality Assessment (IQA) algorithms evaluate the perceptual qualit...
Stereo images have been captured primarily for 3D reconstruction in the ...
Stereo depth estimation is error-prone; hence, effective error detection...