690 citations · 1.6k across the 19 of their papers we have counts for
20 papers
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…
Localization of Just Noticeable Difference for Image Compression
Guangan Chen, Hanhe Lin, Oliver Wiedemann +1
The just noticeable difference (JND) is the minimal difference between stimuli that can be detected by a person. The picture-wise just noticeable difference (PJND) for a given refe…
Relaxed forced choice improves performance of visual quality assessment methods
Mohsen Jenadeleh, Johannes Zagermann, Harald Reiterer +3
In image quality assessment, a collective visual quality score for an image or video is obtained from the individual ratings of many subjects. One commonly used format for these ex…
KonX: Cross-Resolution Image Quality Assessment
Oliver Wiedemann, Vlad Hosu, Shaolin Su +1
Scale-invariance is an open problem in many computer vision subfields. For example, object labels should remain constant across scales, yet model predictions diverge in many cases.…
Going the Extra Mile in Face Image Quality Assessment: A Novel Database and Model
Shaolin Su, Hanhe Lin, Vlad Hosu +6
An accurate computational model for image quality assessment (IQA) benefits many vision applications, such as image filtering, image processing, and image generation. Although the…
TranSalNet: Towards perceptually relevant visual saliency prediction
Jianxun Lou, Hanhe Lin, David Marshall +2
Visual saliency prediction using transformers - Convolutional neural networks (CNNs) have significantly advanced computational modelling for saliency prediction. However, accuratel…