Jiebin Yan
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View article: Computational Analysis of Degradation Modeling in Blind Panoramic Image Quality Assessment
Computational Analysis of Degradation Modeling in Blind Panoramic Image Quality Assessment Open
Blind panoramic image quality assessment (BPIQA) has recently brought a new challenge to the visual quality community, due to the complex interaction between immersive content and human behavior. Although many efforts have been made to adv…
View article: Computational Analysis of Degradation Modeling in Blind Panoramic Image Quality Assessment
Computational Analysis of Degradation Modeling in Blind Panoramic Image Quality Assessment Open
Blind panoramic image quality assessment (BPIQA) has recently brought new challenge to the visual quality community, due to the complex interaction between immersive content and human behavior. Although many efforts have been made to advan…
View article: Max360IQ: Blind Omnidirectional Image Quality Assessment with Multi-axis Attention
Max360IQ: Blind Omnidirectional Image Quality Assessment with Multi-axis Attention Open
Omnidirectional image, also called 360-degree image, is able to capture the entire 360-degree scene, thereby providing more realistic immersive feelings for users than general 2D image and stereoscopic image. Meanwhile, this feature brings…
View article: Subjective and Objective Quality Assessment of Non-Uniformly Distorted Omnidirectional Images
Subjective and Objective Quality Assessment of Non-Uniformly Distorted Omnidirectional Images Open
Omnidirectional image quality assessment (OIQA) has been one of the hot topics in IQA with the continuous development of VR techniques, and achieved much success in the past few years. However, most studies devote themselves to the uniform…
View article: Multitask Auxiliary Network for Perceptual Quality Assessment of Non-Uniformly Distorted Omnidirectional Images
Multitask Auxiliary Network for Perceptual Quality Assessment of Non-Uniformly Distorted Omnidirectional Images Open
Omnidirectional image quality assessment (OIQA) has been widely investigated in the past few years and achieved much success. However, most of existing studies are dedicated to solve the uniform distortion problem in OIQA, which has a natu…
View article: Video Quality Assessment for Online Processing: From Spatial to Temporal Sampling
Video Quality Assessment for Online Processing: From Spatial to Temporal Sampling Open
With the rapid development of multimedia processing and deep learning technologies, especially in the field of video understanding, video quality assessment (VQA) has achieved significant progress. Although researchers have moved from desi…
View article: Meta-Point Learning and Refining for Category-Agnostic Pose Estimation
Meta-Point Learning and Refining for Category-Agnostic Pose Estimation Open
Category-agnostic pose estimation (CAPE) aims to predict keypoints for arbitrary classes given a few support images annotated with keypoints. Existing methods only rely on the features extracted at support keypoints to predict or refine th…
View article: Perceptual Quality Assessment of Omnidirectional Images
Perceptual Quality Assessment of Omnidirectional Images Open
Omnidirectional images, also called 360◦images, have attracted extensive attention in recent years, due to the rapid development of virtual reality (VR) technologies. During omnidirectional image processing including capture, transmission,…
View article: Super Resolution Image Visual Quality Assessment Based on Feature Optimization
Super Resolution Image Visual Quality Assessment Based on Feature Optimization Open
Most existing no-referenced image quality assessment (NR-IQA) algorithms need to extract features first and then predict image quality. However, only a small number of features work in the model, and the rest will degrade the model perform…
View article: Perceptually Optimized Deep High-Dynamic-Range Image Tone Mapping
Perceptually Optimized Deep High-Dynamic-Range Image Tone Mapping Open
We describe a deep high-dynamic-range (HDR) image tone mapping operator that is computationally efficient and perceptually optimized. We first decompose an HDR image into a normalized Laplacian pyramid, and use two deep neural networks (DN…
View article: Exposing Semantic Segmentation Failures via Maximum Discrepancy Competition
Exposing Semantic Segmentation Failures via Maximum Discrepancy Competition Open
Semantic segmentation is an extensively studied task in computer vision, with numerous methods proposed every year. Thanks to the advent of deep learning in semantic segmentation, the performance on existing benchmarks is close to saturati…
View article: Learning a No-Reference Quality Predictor of Stereoscopic Images by Visual Binocular Properties
Learning a No-Reference Quality Predictor of Stereoscopic Images by Visual Binocular Properties Open
In this work, we develop a novel no-reference (NR) quality assessment metric for stereoscopic images based on monocular and binocular features, motivated by visual perception properties of the human visual system (HVS) named binocular riva…