activity
20182024
most citedProgressive Knowledge Transfer Based on Human Visual Perception Mechanism for Perceptual Quality Assessment of Point Clouds

4 citations · 5 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV20224 cited

Progressive Knowledge Transfer Based on Human Visual Perception Mechanism for Perceptual Quality Assessment of Point Clouds

Qi Liu, Yiyun Liu, Honglei Su +2

With the wide applications of colored point cloud in many fields, point cloud perceptual quality assessment plays a vital role in the visual communication systems owing to the exis…

cs.HC2022

Review of Serious Games for Medical Operation

Huansheng Ning, Zhijie Guo, Raouf Hamzaoui +3

Medical operations (MOs) are essential in healthcare,and they are also a big concept that includes various operations during the perioperative period.Traditional operation exposes…

eess.IV2020

Reduced Reference Perceptual Quality Model and Application to Rate Control for 3D Point Cloud Compression

Qi Liu, Hui Yuan, Raouf Hamzaoui +3

In rate-distortion optimization, the encoder settings are determined by maximizing a reconstruction quality measure subject to a constraint on the bit rate. One of the main challen…

eess.IV2020

Model-based Joint Bit Allocation between Geometry and Color for Video-based 3D Point Cloud Compression

Qi Liu, Hui Yuan, Junhui Hou +2

Rate distortion optimization plays a very important role in image/video coding. But for 3D point cloud, this problem has not been investigated. In this paper, the rate and distorti…

cs.MM2020

SUR-FeatNet: Predicting the Satisfied User Ratio Curvefor Image Compression with Deep Feature Learning

Hanhe Lin, Vlad Hosu, Chunling Fan +4

The satisfied user ratio (SUR) curve for a lossy image compression scheme, e.g., JPEG, characterizes the complementary cumulative distribution function of the just noticeable diffe…

cs.CL2018

Image-based Natural Language Understanding Using 2D Convolutional Neural Networks

Erinc Merdivan, Anastasios Vafeiadis, Dimitrios Kalatzis +8

We propose a new approach to natural language understanding in which we consider the input text as an image and apply 2D Convolutional Neural Networks to learn the local and global…