GraphIQA: Learning distortion graph representations for blind image quality assessment
A good distortion representation is crucial for the success of deep blind image quality
assessment (BIQA). However, most previous methods do not effectively model the …
assessment (BIQA). However, most previous methods do not effectively model the …
Gpa-net: No-reference point cloud quality assessment with multi-task graph convolutional network
With the rapid development of 3D vision, point cloud has become an increasingly popular
3D visual media content. Due to the irregular structure, point cloud has posed novel …
3D visual media content. Due to the irregular structure, point cloud has posed novel …
MMMNet: An end-to-end multi-task deep convolution neural network with multi-scale and multi-hierarchy fusion for blind image quality assessment
As the evaluation of image quality depends on the human visual system (HVS), many
existing image quality assessment (IQA) methods focus on modeling the HVS to account for …
existing image quality assessment (IQA) methods focus on modeling the HVS to account for …
Subjective and objective quality assessment for in-the-wild computer graphics images
Computer graphics images (CGIs) are artificially generated by means of computer programs
and are widely perceived under various scenarios, such as games, streaming media, etc. In …
and are widely perceived under various scenarios, such as games, streaming media, etc. In …
Hel** Visually Impaired People Take Better Quality Pictures
M Mandal, D Ghadiyaram, D Gurari… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Perception-based image analysis technologies can be used to help visually impaired
people take better quality pictures by providing automated guidance, thereby empowering …
people take better quality pictures by providing automated guidance, thereby empowering …
Staged-learning: Assessing the quality of screen content images from distortion information
The small volume of the existing screen content images (SCIs) database with human ratings
restricts the training processes of no-reference (NR) image quality assessment models …
restricts the training processes of no-reference (NR) image quality assessment models …
End-to-end image patch quality assessment for image/video with compression artifacts
TT Pham, X Van Hoang, NT Nguyen, DT Dinh - IEEE Access, 2020 - ieeexplore.ieee.org
In this paper, we present an experimental image quality assessment (IQA) method for
image/video patches with compression artifacts. Using the High Efficiency Video Coding …
image/video patches with compression artifacts. Using the High Efficiency Video Coding …
No-Reference image quality assessment based on image multi-scale contour prediction
Accurately assessing image quality is a challenging task, especially without a reference
image. Currently, most of the no-reference image quality assessment methods still require …
image. Currently, most of the no-reference image quality assessment methods still require …
Deep multi-task learning for image/video distortions identification
Identifying distortions in images and videos is important and useful in various visual
applications, such as image quality enhancement and assessment techniques. Instead of …
applications, such as image quality enhancement and assessment techniques. Instead of …
Local sharpness failure detection of camera module lens based on image blur assessment
F Wang, J Chen, Z **e, Y Ai, W Zhang - Applied Intelligence, 2023 - Springer
Videos and images have been widely used, and the requirements for camera imaging
quality are getting higher and higher. At present, most methods of camera lens sharpness …
quality are getting higher and higher. At present, most methods of camera lens sharpness …