IEEE Journal of Selected Topics in Signal Processing
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IEEE Journal of Selected Topics in Signal Processing Publication Information
Publication Year: 2023,Page(s):C2 - C2
IEEE Journal of Selected Topics in Signal Processing Publication Information
Year: 2023 | Volume: 17 | Issue: 6
Table of Contents
Year: 2023 | Volume: 17 | Issue: 6
Editorial Advancements in Learning-Based Quality Prediction for Advanced Visual Media
Aladine Chetouani;Sebastian Bosse;Patrick Le Callet;Mylene Farias;Johannes Ballé;Jing Li
Publication Year: 2023,Page(s):1148 - 1149
Attentive Deep Image Quality Assessment for Omnidirectional Stitching
Huiyu Duan;Xiongkuo Min;Wei Sun;Yucheng Zhu;Xiao-Ping Zhang;Guangtao Zhai
Publication Year: 2023,Page(s):1150 - 1164
Cited by: Papers (22)
Omnidirectional images or videos are commonly generated via the stitching of multiple images or videos, and the quality of omnidirectional stitching strongly influences the quality of experience (QoE) of the generated scenes. Although there were many studies research the omnidirectional image quality assessment (IQA), the evaluation of the omnidirectional stitching quality has not been sufficientl...Show More
Blind Image Quality Assessment via Deep Response Feature Decomposition and Aggregation
Hui Wang;Guangcheng Wang;Wenjun Xia;Ziyuan Yang;Hui Yu;Leyuan Fang;Yi Zhang
Publication Year: 2023,Page(s):1165 - 1177
Cited by: Papers (2)
Image quality is related to image content and distortion information. Most learning-based image quality assessment (IQA) methods extract quality-oriented features with auxiliary tasks like detecting the distortion type and level. However, the perceptual quality degradation caused by the same distortion type and level varies substantially for different content in an image. To deal with this problem...Show More
Blind Quality Assessment for in-the-Wild Images via Hierarchical Feature Fusion and Iterative Mixed Database Training
Publication Year: 2023,Page(s):1178 - 1192
Cited by: Papers (52)
Image quality assessment (IQA) is very important for both end-users and service providers since a high-quality image can significantly improve the user's quality of experience (QoE) and also benefit lots of computer vision algorithms. Most existing blind image quality assessment (BIQA) models were developed for synthetically distorted images, however, they perform poorly on in-the-wild images, whi...Show More
PVBLiF: A Pseudo Video-Based Blind Quality Assessment Metric for Light Field Image
Publication Year: 2023,Page(s):1193 - 1207
Cited by: Papers (4)
Going beyond traditional 2D imaging is not only an emerging trend of imaging technology, but also the key to a more immersive user experience. Light Field Image (LFI) is a typical high-dimensional imaging format, and the quality evaluation of which is very challenging but necessary. In this article, we propose a novel Pseudo Video-based Blind quality assessment metric for Light Field image (PVBLiF...Show More
Measuring the Consistency and Diversity of 3D Face Generation
Kunlin Liu;Wenbo Zhou;Zhenyu Zhang;Yanhao Ge;Hao Tang;Weiming Zhang;Nenghai Yu
Publication Year: 2023,Page(s):1208 - 1220
Cited by: Papers (1)
3D-aware GANs have shown their impressive power on 3D controlling for synthesized portraits. While the plausible facial reality is achieved, the inherent 3D properties of the generated results have actually not been well analyzed. One of the reasons is that the wildly-used metrics, such as Inception Score (IS) or Fréchet Inception Distance (FID), focus more on the perceptual features rather than e...Show More
Can Perceptual Guidance Lead to Semantically Explainable Adversarial Perturbations?
Charantej Reddy Pochimireddy;Aditya T. Siripuram;Sumohana S. Channappayya
Publication Year: 2023,Page(s):1221 - 1231
It is well known that carefully crafted imperceptible perturbations can cause state-of-the-art deep learning classification models to misclassify. Understanding and analyzing these adversarial perturbations play a crucial role in the design of robust convolutional neural networks. However, their mechanics are not well understood. In this article, we investigate the following question: Is there any...Show More
StableFace: Analyzing and Improving Motion Stability for Talking Face Generation
Jun Ling;Xu Tan;Liyang Chen;Runnan Li;Yuchao Zhang;Sheng Zhao;Li Song
Publication Year: 2023,Page(s):1232 - 1247
Cited by: Papers (6)
While previous methods for speech-driven talking face generation have shown significant advances in improving the visual and lip-sync quality of the synthesized videos, they have paid less attention to lip motion jitters which can substantially undermine the perceived quality of talking face videos. What causes motion jitters, and how to mitigate the problem? In this article, we conduct systematic...Show More
Index-Modulated Metasurface Transceiver Design Using Reconfigurable Intelligent Surfaces for 6G Wireless Networks
John A. Hodge;Kumar Vijay Mishra;Brian M. Sadler;Amir I. Zaghloul
Publication Year: 2023,Page(s):1248 - 1263
Cited by: Papers (8)
Higher spectral and energy efficiencies are the envisioned defining characteristics of high data-rate sixth-generation (6G) wireless networks. One of the enabling technologies to meet these requirements is index modulation (IM), which transmits information through permutations of indices of spatial, frequency, or temporal media. In this paper, we propose novel electromagnetics-compliant designs of...Show More
Seg-DGDNet: Segmentation Based Disguise Guided Dropout Network for Low Resolution Face Recognition
Muskan Dosi;Chiranjeev Chiranjeev;Shivang Agarwal;Jyoti Chaudhary;Sunny Manchanda;Kavita Balutia;Kaushik Bhagwatkar;Mayank Vatsa;Richa Singh
Publication Year: 2023,Page(s):1264 - 1276
Cited by: Papers (5)
Face recognition models often encounter challenges while recognizing partially occluded faces. Disguise can be manifested intentionally to impersonate someone or unintentionally when the subject wears artifacts such as sunglasses, masks, hats, and caps. To identify a subject accurately, it is essential to discard the occluded regions of the subject's face and use the features extracted from the vi...Show More
List of Reviewers
Year: 2023 | Volume: 17 | Issue: 6
2023 Index IEEE Journal of Selected Topics in Signal Processing Vol. 17
Publication Year: 2023,Page(s):1281 - 1299_lpage_
2023 Index IEEE Journal of Selected Topics in Signal Processing Vol. 17
Year: 2023 | Volume: 17 | Issue: 6
IEEE Signal Processing Society Information
Year: 2023 | Volume: 17 | Issue: 6
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