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3D No-reference Image Quality Assessment via Transfer Learning and Saliency-guided Feature Consolidation

Xu Xiaogang, Bufan Shi, Zijin Gu, Ruizhe Deng, Xiaodong Chen, Andrey S. Krylov, Yong Ding
2019 IEEE Access  
Motivated by the success of convolutional neural networks (CNNs) in image-related applications, in this paper, we design an effective method for no-reference 3D image quality assessment (3D IQA) through  ...  INDEX TERMS No-reference 3D image quality assessment, deep neural network, transfer learning.  ...  The framework of our 3D NR-IQA algorithm is illustrated in Fig. 2 , where quality-aware features are extracted by CNN fine-tuning strategy and consolidated by a saliency-guided approach.  ... 
doi:10.1109/access.2019.2925084 fatcat:hmh2qz5tqfhbpfmbs4wx6r7ykm

VCIP 2020 Index

2020 2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)  
Decomposition Yu, Zengrui Attention-Guided Fusion Network of Point Clou and Multiple Views for 3D Shape Recognition Yue, Guanghui No-Reference Stereoscopic Image Quality Assessment Considering  ...  On 2D-3D Image Feature Detections for Image To-Geometry Registration in Virtual Dental Mod Lee, Chan-Ho Deep Temporal Color Constancy for AC Light Sources Lei, Jianjun Attention-Guided Fusion Network  ... 
doi:10.1109/vcip49819.2020.9301896 fatcat:bdh7cuvstzgrbaztnahjdp5s5y

Stereoscopic visual saliency prediction based on stereo contrast and stereo focus

Hao Cheng, Jian Zhang, Qiang Wu, Ping An, Zhi Liu
2017 EURASIP Journal on Image and Video Processing  
We propose a visual saliency prediction model for stereoscopic images based on stereo contrast and stereo focus models.  ...  In this paper, we exploit two characteristics of stereoscopic vision: the pop-out effect and the comfort zone.  ...  One supplies high-quality stereoscopic images and the other supplies low-quality stereoscopic images generated by Kinect-1.  ... 
doi:10.1186/s13640-017-0210-5 fatcat:zg26cy2d3rdmneeczkedf3a3zq

Hybrid Distortion Aggregated Visual Comfort Assessment for Stereoscopic Image Retargeting [article]

Ya Zhou, Zhibo Chen, Weiping Li
2018 arXiv   pre-print
Finally, the semantic distortion is represented by the correlation distance of paired feature maps extracted from original stereoscopic image and its retargeted image by using trained deep neural network  ...  We validate the effectiveness of HDA-VCA on published Stereoscopic Image Retargeting Database (SIRD) and two stereoscopic image databases IEEE-SA and NBU 3D-VCA.  ...  In recent years, 3D visual comfort quality assessment has attracted much attention. Some VCA models for stereoscopic images have been proposed.  ... 
arXiv:1811.12687v1 fatcat:643ydzywcbbfdjgrauaqfirjjy

2D and 3D Image Quality Assessment: A Survey of Metrics and Challenges

Yuzhen Niu, Yini Zhong, Wenzhong Guo, Yiqing Shi, Peikun Chen
2019 IEEE Access  
The main factors that affect 2D image quality are fidelity and aesthetics. Another main factor that affects stereoscopic 3D image quality is visual comfort.  ...  Image quality is important not only for the viewing experience, but also for the performance of image processing algorithms.  ...  [40] presented a weighted average deep image quality measure for FR-IQA (WaDIQaM-FR).  ... 
doi:10.1109/access.2018.2885818 fatcat:gjq7vdwczffufmk3smmn7mokgi

Perceptual image quality assessment: a survey

Guangtao Zhai, Xiongkuo Min
2020 Science China Information Sciences  
Third, the performances of the state-of-the-art quality measures for visual signals are compared with an introduction of the evaluation protocols.  ...  Specifically, the frequently used subjective image quality assessment databases are first reviewed, as they serve as the validation set for the objective measures.  ...  Stereoscopic image quality assessment Stereoscopic or 3D IQA is popularized with the development of 3D movies and TV programs.  ... 
doi:10.1007/s11432-019-2757-1 fatcat:kizmju2lbbbcxjb42y6stct5sq

Related Work on Image Quality Assessment [article]

Dongxu Wang
2021 arXiv   pre-print
According to whether the reference image is complete and available, image quality evaluation can be divided into three categories: Full-Reference(FR), Reduced- Reference(RR), and Non- Reference(NR).  ...  Due to the existence of quality degradations introduced in various stages of visual signal acquisition, compression, transmission and display, image quality assessment (IQA) plays a vital role in image-based  ...  [28] proposed an end-to-end saliency-guided deep neural network (SGDNet) for no-reference image quality assessment (NR-IQA).  ... 
arXiv:2111.06291v1 fatcat:a3wrhqws7bg5thadvagtqvwl3q

Intelligent Visual Media Processing: When Graphics Meets Vision

Ming-Ming Cheng, Qi-Bin Hou, Song-Hai Zhang, Paul L. Rosin
2017 Journal of Computer Science and Technology  
for 2D image understanding and 3D model analysis.  ...  processing tools, such as deep neural networks, provide effective ways for learning how to deal with heterogeneous visual data; iii) new data capture devices, such as the Kinect, bridge between algorithms  ...  Acknowledgments We would like to thank the anonymous reviewers for their useful feedback.  ... 
doi:10.1007/s11390-017-1681-7 fatcat:j6u7dzfbhfgnlpnluqajjbaxy4

A proto-object based saliency model in three-dimensional space

Brian Hu, Ralinkae Kane-Jackson, Ernst Niebur
2016 Vision Research  
Most models of visual saliency operate on two-dimensional images, using elementary image features such as intensity, color, or orientation.  ...  In this report we extend a model of proto-object based saliency to include depth information and evaluate its performance on three separate three-dimensional eye tracking datasets.  ...  We would like to thank Tam Nguyen, Romuald Pépion, and Chi-Yao Ma for helpful discussions about their code and datasets, and Rüdiger von der Heydt for sharing his deep insights on vision with us.  ... 
doi:10.1016/j.visres.2015.12.004 pmid:26739278 pmcid:PMC4749459 fatcat:edangjzxbja5vn53nx4kzt6fqy

RGB-D salient object detection: A survey

Tao Zhou, Deng-Ping Fan, Ming-Ming Cheng, Jianbing Shen, Ling Shao
2021 Computational Visual Media  
All collected models, benchmark datasets, datasets constructed for attribute-based evaluation, and related code are publicly available at https://github.com/taozh2017/RGBD-SODsurvey.  ...  Finally, we discuss several challenges and open directions of RGB-D based salient object detection for future research.  ...  Acknowledgements This research was supported by a Major Project for a New Generation of AI under Grant No. 2018AAA0100400, National Natural Science Foundation of China (61922046), and Tianjin Natural Science  ... 
doi:10.1007/s41095-020-0199-z pmid:33432275 pmcid:PMC7788385 fatcat:foiz2zth4vckjfuhvh524hwdtq

2020 Index IEEE Transactions on Multimedia Vol. 22

2020 IEEE transactions on multimedia  
Multi-View Saliency Guided Deep Neural Network for 3-D Object Retrieval and Classification.  ...  ., +, TMM July 2020 1667-1679 Learning Local Quality-Aware Structures of Salient Regions for Stereoscopic Images via Deep Neural Networks.  ...  Image watermarking Blind Watermarking for 3-D Printed Objects by Locally Modifying Layer Thickness. 2780 -2791 Low-Light Image Enhancement With Semi-Decoupled Decomposition.  ... 
doi:10.1109/tmm.2020.3047236 fatcat:llha6qbaandfvkhrzpe5gek6mq

RGB-D Salient Object Detection: A Survey [article]

Tao Zhou, Deng-Ping Fan, Ming-Ming Cheng, Jianbing Shen, Ling Shao
2020 arXiv   pre-print
All collected models, benchmark datasets, source code links, datasets constructed for attribute-based evaluation, and codes for evaluation will be made publicly available at https://github.com/taozh2017  ...  Finally, we discuss several challenges and open directions of RGB-D based SOD for future research.  ...  The authors first collected 1,250 stereoscopic images from Flickr 1 , NVIDIA 3D Vision Live 2 , and Stereoscopic Image Gallery 3 .  ... 
arXiv:2008.00230v3 fatcat:n52weyun25fq3aug4ughjqs2ru

Table of contents

2020 IEEE Transactions on Image Processing  
Lau 1827 Efficient Evaluation of Image Quality via Deep-Learning Approximation of Perceptual Metrics ......................... ..........................................................................  ...  Ye 5711 Learning to Explore Saliency for Stereoscopic Videos Via Component-Based Interaction ................................. ............................................................. Q.  ... 
doi:10.1109/tip.2019.2940372 fatcat:h23ul2rqazbstcho46uv3lunku

2020 Index IEEE Transactions on Image Processing Vol. 29

2020 IEEE Transactions on Image Processing  
., +, TIP 2020 3927-3940 Efficient Evaluation of Image Quality via Deep-Learning Approximation of Perceptual Metrics.  ...  ., +, TIP 2020 2287-2300 Learning to Explore Saliency for Stereoscopic Videos Via Component-Based Interaction.  ... 
doi:10.1109/tip.2020.3046056 fatcat:24m6k2elprf2nfmucbjzhvzk3m

Visual saliency detection for RGB-D images under a Bayesian framework

Songtao Wang, Zhen Zhou, Wei Jin, Hanbing Qu
2018 IPSJ Transactions on Computer Vision and Applications  
By analysing 3D saliency in the case of RGB images and depth images, the class-conditional mutual information is computed for measuring the dependence of deep features extracted using a convolutional neural  ...  In this paper, we propose a saliency detection model for RGB-D images based on the deep features of RGB images and depth images within a Bayesian framework.  ...  Acknowledgements This work was supported in part by the Beijing Municipal special financial project (PXM2016_278215_000013, ZLXM_2017C010) and by the Innovation Group Plan of Beijing Academy of Science  ... 
doi:10.1186/s41074-017-0037-0 fatcat:jklxzq46vrbh3mk6n7ocbqhoiu
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