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- AIM 2019 Challenge on Real-World Image Super-Resolution: Methods and Results110
The AIM 2019 challenge on real world super-resolution addresses the real world setting, where paired true high and low-resolution images are unavailable, and aims to advance the state-of-the-art and provide a standard benchmark for this newly emerging task.
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- AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results101
The AIM 2020 challenge on efficient single image super-resolution was to super-resolve an input image with a magnification factor x4 based on a set of prior examples of low and corresponding high resolution images with focus on the proposed solutions and results.
- A Gated Peripheral-Foveal Convolutional Neural Network for Unified Image Aesthetic Prediction100
A gated peripheral-foveal convolutional neural network that aims to mimic the functions of peripheral vision to encode the holistic information and provide the attended regions for the fovea and a gated information fusion network to weigh their contributions.
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- Haze removal for a single visible remote sensing image90
The evaluation results with qualitative and quantitative assessments demonstrate that the proposed method is superior to the traditional methods, and can recover a haze-free image with high quality.
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- No Reference Quality Assessment for Screen Content Images Using Stacked Autoencoders in Pictorial and Textual Regions78
An effective and novel blind quality evaluation metric for SCIs by using stacked autoencoders (SAE) based on pictorial and textual regions based on a weighted model is presented.
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- No-reference image quality assessment in contourlet domain75
The contourlet transform is utilized to NSS of images, and then the relationship of contour let coefficients is represented by the joint distribution, and an image-dependent threshold is adopted to reduce the effect of content to the statistical model.
- Image quality assessment and human visual system72
This paper summaries the state-of-the-art of image quality assessment (IQA) and human visual system (HVS) and introduces the basic theories and development histories of the above two kinds of HVS-based IQA methods.
- Interpretable Detail-Fidelity Attention Network for Single Image Super-Resolution66
A purposeful and interpretable detail-fidelity attention network to progressively process these smoothes and details in a divide-and-conquer manner, which is a novel and specific prospect of image super-resolution for the purpose of improving detail fidelity.
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- A Blind Stereoscopic Image Quality Evaluator With Segmented Stacked Autoencoders Considering the Whole Visual Perception Route58
A Deep Edge and COlor Signal INtegrity Evaluator (DECOSINE) based on the whole visual perception route from eyes to the frontal lobe and especially focus on the edge and color signal processing in retinal ganglion cells and lateral geniculate nucleus is proposed.
- NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results54
This paper reviews the NTIRE 2020 challenge on perceptual extreme super-resolution with focus on proposed solutions and results and gauges the state-of-the-art in single image super- resolution.
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- 3D Panoramic Virtual Reality Video Quality Assessment Based on 3D Convolutional Neural Networks53
A free available data set (VRQ-TJU) for VR quality assessment is proposed with subjective scores for each sample data and an end-to-end 3-D convolutional neural network is introduced to predict the VR video quality without a referenced VR video.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-15. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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