32 citations · 68 across the 8 of their papers we have counts for
5 papers · 1 filter
PC-JND: Subjective Study and Dataset on Just Noticeable Difference for Point Clouds in 6DoF Virtual Reality
Chunling Fan, Yun Zhang, Dietmar Saupe +2
The Just Noticeable Difference (JND) accounts for the minimum distortion at which humans can perceive a difference between a pristine stimulus and its distorted version. The JND co…
Comment on "No-Reference Video Quality Assessment Based on the Temporal Pooling of Deep Features"
Franz Götz-Hahn, Vlad Hosu, Dietmar Saupe
In Neural Processing Letters 50,3 (2019) a machine learning approach to blind video quality assessment was proposed. It is based on temporal pooling of features of video frames, ta…
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…
KonVid-150k: A Dataset for No-Reference Video Quality Assessment of Videos in-the-Wild
Franz Götz-Hahn, Vlad Hosu, Hanhe Lin +1
Video quality assessment (VQA) methods focus on particular degradation types, usually artificially induced on a small set of reference videos. Hence, most traditional VQA methods u…
Recovering Missing Coefficients in DCT-Transformed Images
Shujun Li, Andreas Karrenbauer, Dietmar Saupe +1
A general method for recovering missing DCT coefficients in DCT-transformed images is presented in this work. We model the DCT coefficients recovery problem as an optimization prob…