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Found 5 papers, 1 papers with code
Half of an image is enough for quality assessment
Deep networks have demonstrated promising results in the field of Image Quality Assessment (IQA).
Apples and Oranges? Assessing Image Quality over Content Recognition
A sequential spatial-channel attention module is proposed to simulate the visual attention and contrast sensitivity mechanisms that are crucial for content recognition and quality assessment.
Visual Mechanisms Inspired Efficient Transformers for Image and Video Quality Assessment
Meanwhile, representative features for image quality perception in the spatial and frequency domains can also be derived from the IQA model, which are then fed into another windowed transformer architecture for video quality assessment (VQA).
Consumer Image Quality Prediction using Recurrent Neural Networks for Spatial Pooling
Promising results for subjective image quality prediction have been achieved during the past few years by using convolutional neural networks (CNN).
Transformer for Image Quality Assessment
Transformer has become the new standard method in natural language processing (NLP), and it also attracts research interests in computer vision area.
