EDBT 2026 Demo / reviewers in the wild / expert
Qizheng Yuan
dblp:214/5859
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Image and video coding · 67% Multimedia systems and quality of experience · 33% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Multimedia systems and quality of experience › video quality assessment
no-reference video quality assessment |
0.3 | 1 | 2018 | No-Reference View Synthesis Quality Prediction for 3-D Videos Based on Color-Depth Interactions · IEEE Trans. Multim. 2018 |
Image and video coding
quality assessment |
0.3 | 1 | 2018 | No-Reference View Synthesis Quality Prediction for 3-D Videos Based on Color-Depth Interactions · IEEE Trans. Multim. 2018 |
Image and video coding › quality assessment
synthesized view quality assessment |
0.3 | 1 | 2018 | No-Reference View Synthesis Quality Prediction for 3-D Videos Based on Color-Depth Interactions · IEEE Trans. Multim. 2018 |
Methods — techniques the papers use, named apart from their topics
color-depth interaction modeling · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | No-Reference View Synthesis Quality Prediction for 3-D Videos Based on Color-Depth InteractionsabstractIn a 3-D video system, automatically predicting the quality of synthesized 3-D video based on the inputs of color and depth videos is an urgent but very difficult task, while the existing full-reference methods usually measure the perceptual quality of the synthesized video. In this paper, a high-efficiency view synthesis quality prediction (HEVSQP) metric for view synthesis is proposed. Based on the derived VSQP model that quantifies the influences of color and depth distortions and their interactions in determining the perceptual quality of 3-D synthesized video, color-involved VSQP and depth-involved VSQP indices are predicted, respectively, and are combined to yield an HEVSQP index. Experimental results on our constructed NBU-3D Synthesized Video Quality Database demonstrate that the proposed HEVSOP has good performance evaluated on the entire synthesized video-quality database, compared with other full-reference and no-reference video-quality assessment metrics. Feng Shao 0001, Qizheng Yuan, Weisi Lin, Gangyi Jiang |
IEEE Trans. Multim. | 2 |