activity
20192023
most citedSaliency-Aware Spatio-Temporal Artifact Detection for Compressed Video Quality Assessment

19 citations · 23 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV2023

Geometry-based spherical JND modeling for 360 display

Hongan Wei, Jiaqi Liu, Bo Chen +3

360 videos have received widespread attention due to its realistic and immersive experiences for users. To date, how to accurately model the user perceptions on 360…

eess.IV2023★ 19 cited

Saliency-Aware Spatio-Temporal Artifact Detection for Compressed Video Quality Assessment

Liqun Lin, Yang Zheng, Weiling Chen +2

Compressed videos often exhibit visually annoying artifacts, known as Perceivable Encoding Artifacts (PEAs), which dramatically degrade video visual quality. Subjective and objecti…

cs.MM2022★ 1 cited

Timestamp-independent Haptic-Visual Synchronization

Yiwen Xu, Liangtao Huang, Tiesong Zhao +2

The booming haptic data significantly improves the users'immersion during multimedia interaction. As a result, the study of Haptic,Audio-Visual Environment(HAVE)has attracted atten…

eess.IV2022

Deep Quality Assessment of Compressed Videos: A Subjective and Objective Study

Liqun Lin, Zheng Wang, Jiachen He +3

In the video coding process, the perceived quality of a compressed video is evaluated by full-reference quality evaluation metrics. However, it is difficult to obtain reference vid…

cs.CV2019★ 3 cited

PEA265: Perceptual Assessment of Video Compression Artifacts

Liqun Lin, Shiqi Yu, Tiesong Zhao +1

The most widely used video encoders share a common hybrid coding framework that includes block-based motion estimation/compensation and block-based transform coding. Despite their…