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检索条件"任意字段=2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023"

共 2296 条记录，以下是121-130 订阅

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Inter-Observer visual Congruency in Video-Viewing

Inter-Observer Visual Congruency in Video-Viewing

引用

ieee international conference on visual communications and image processing (vcip) - visual communications in the Era of AI and Limited Resources

作者： Yue, Jiaomin Lu, Qiang Zhu, Dandan Min, Xiongkuo Zhang, Xiao-Ping Zhai, Guangtao Shanghai Jiao Tong Univ Inst Image Commun & Network Engn Shanghai Peoples R China Ryerson Univ Dept Elect Comp & Biomed Engn Toronto ON Canada

ISBN: (纸本)9781728185514

There are individual differences in human visual attention between observers when viewing the same scene. Inter-observer visual congruency (IOVC) describes the dispersion between different people's visual attention areas when they observe the same stimulus. Research on the IOVC of video is interesting but lacking. In this paper, we first introduce the measurement to calculate the IOVC of video. And an eye-tracking experiment is conducted in a realistic movie-watching environment to establish a movie scene dataset. Then we propose a method to predict the IOVC of video, which employs a dual-channel network to extract and integrate content and optical flow features. The effectiveness of the proposed prediction model is validated on our dataset. And the correlation between inter-observer congruency and video emotion is analyzed.

关键词： Inter-observer visual congruency visual attention neural network movie analysis

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image Inpainting with Frequency Domain Wavelet Convolution

Image Inpainting with Frequency Domain Wavelet Convolution

引用

ieee international conference on visual communications and image processing (vcip)

作者： Huang, Jain-Kai Liu, Tsung-Jung Liu, Kuan-Hsien Natl Chung Hsing Univ Dept Comp Sci & Engn Taichung Taiwan Natl Chung Hsing Univ Dept Elect Engn Taichung Taiwan Natl Chung Hsing Univ Grad Inst Commun Engn Taichung Taiwan Natl Taichung Univ Sci & Technol Dept Comp Sci & Informat Engn Taichung Taiwan

ISBN: (纸本)9781665475921

This paper used Time-Frequency Analysis (TFA) techniques for signal processing on tasks of computer vision. Our main idea is as follows: To build a simple network architecture without two or more convolutional neural networks (CNNs), analyze hidden features by Discrete Wavelet Transform (DWT), and send them into filters as weights by convolutions, transformers or other methods. And we do not need to build the network with 2 or more stages to accomplish this idea. Actually, we try to directly use TFA skills on CNN to build one-stage network. Networks which build by this way not only keep their outstanding performance, but also cost lower computing resources. In this paper, we mainly use DWT on CNN to solve image inpainting problems. And the results show that our model can work stably in frequency domain to realize free-form image inpainting.

关键词： image Inpainting Signal processing Computer Vision Deep Learning Neural Network

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Rate Adaptation for Learned Two-layer B-frame Coding without Signaling Motion Information

Rate Adaptation for Learned Two-layer B-frame Coding without...

引用

2023 ieee international conference on visual communications and image processing, vcip 2023

作者： Xie, Hong-Sheng Chen, Yi-Hsin Peng, Wen-Hsiao Benjak, Martin Ostermann, Jorn National Yang Ming Chiao Tung University Taiwan Leibniz Universität Hannover Germany

ISBN: (纸本)9798350359855

This paper explores the potential of a learned two-layer B-frame codec, known as TLZMC. TLZMC is one of the few early attempts that deviate from the hybrid-based coding architecture by skipping motion coding. With TLZMC, a low-resolution base layer is utilized to encode temporally unpredictable information. We address the question of whether adapting the base-layer bitrate can achieve better rate-distortion performance. We apply the feature map modulation technique to enable per-frame bitrate adaptation of the base layer. We then propose and compare three online search strategies for determining the base-layer rate parameter: per-level brute-force search, per-level greedy search, and per-frame greedy search. Experimental results show that our top-performing search strategy achieves 0.6%-15.8% Bjontegaard-Delta rate savings over TLZMC. © 2023 ieee.

关键词： image compression

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THE ROLE OF visual ATTENTION IN THE AESTHETIC APPEAL OF CONSUMER imageS: A PRELIMINARY STUDY

THE ROLE OF VISUAL ATTENTION IN THE AESTHETIC APPEAL OF CONS...

引用

ieee international conference on visual communications and image processing (vcip)

作者： Redi, Judith A. Povoa, Isabel Delft Univ Technol NL-2600 AA Delft Netherlands

ISBN: (纸本)9781479902880

Predicting the aesthetic appeal of images is of great interest for a number of applications, from image retrieval to visual quality optimization. In this paper, we report a preliminary study on the relationship between visual attention deployment and aesthetic appeal judgment. In particular, we seek to validate through a scientific approach those simplicity and compositional rules of thumb that have been applied by photographers and modeled by computer vision scientists in computational aesthetics algorithms. Our results provide a confirmation that both simplicity and composition matter for aesthetic appeal of images, and indicate effective ways to compute them directly from the saliency distribution of an image.

关键词： Aesthetic appeal visual attention visual quality image saliency

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Dual-Teacher Color and Structure Distillation for NIR image Colorization

Dual-Teacher Color and Structure Distillation for NIR Image ...

引用

2023 ieee international conference on visual communications and image processing, vcip 2023

作者： Park, Tae-Sung Kim, Jong-Ok Korea University School of Electrical Engineering Seoul Korea Republic of

ISBN: (纸本)9798350359855

Near-infrared (NIR) imaging can acquire more details and textures with less noise in low-light environments compared to RGB. As a result, it has been widely used in low-light vision scenarios such as CCTV, autonomous driving, and military applications. However, applying NIR images to the human cognitive system and computer vision algorithms is challenging due to the lack of color information. Therefore, it is essential to colorize NIR images into RGB ones. We propose a teacher-student deep network with dual-Teacher knowledge distillation to better estimate the original color and structure information. Specifically, our dual-Teacher network is designed to separately teach distinct knowledge, such as color and structure qualities in an image, to the student. Finally, a color guided structure (CGS) and color embedding (CE) module are applied to fuse color and structure features. Our trained model can retain color consistency and detailed structure information of objects. © 2023 ieee.

关键词： Color

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Drone-Based Car Counting via Density Map Learning

Drone-Based Car Counting via Density Map Learning

引用

ieee international conference on visual communications and image processing (vcip)

作者： Huang, Jingxian Ding, Guanchen Guo, Yujia Yang, Daiqin Wang, Sihan Wang, Tao Zhang, Yunfei Wuhan Univ Sch Remote Sensing & Informat Engn Wuhan Peoples R China Tencent Inc Shenzhen 518052 Peoples R China

ISBN: (纸本)9781728180687

Car counting on drone-based images is a challenging task in computer vision. Most advanced methods for counting are based on density maps. Usually, density maps are first generated by convolving ground truth point maps with a Gaussian kernel for later model learning (generation). Then, the counting network learns to predict density maps from input images (estimation). Most studies focus on the estimation problem while overlooking the generation problem. In this paper, a training framework is proposed to generate density maps by learning and train generation and estimation subnetworks jointly. Experiments demonstrate that our method outperforms other density map-based methods and shows the best performance on drone-based car counting.

关键词： Car counting density map learning drone-based image

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Polynomial image-Based Rendering for non-Lambertian Objects

Polynomial Image-Based Rendering for non-Lambertian Objects

引用

ieee international conference on visual communications and image processing (vcip) - visual communications in the Era of AI and Limited Resources

作者： Fachada, Sarah Bonatto, Daniele Teratani, Mehrdad Lafruit, Gauthier Univ Libre Bruxelles Lab Image Synth & Anal Brussels Belgium

ISBN: (纸本)9781728185514

Non-Lambertian objects present an aspect which depends on the viewer's position towards the surrounding scene. Contrary to diffuse objects, their features move non-linearly with the camera, preventing rendering them with existing Depth image-Based Rendering (DIBR) approaches, or to triangulate their surface with Structure-from-Motion (SfM). In this paper, we propose an extension of the DIBR paradigm to describe these non-linearities, by replacing the depth maps by more complete multi-channel "non-Lambertian maps", without attempting a 3D reconstruction of the scene. We provide a study of the importance of each coefficient of the proposed map, measuring the trade-off between visual quality and data volume to optimally render non-Lambertian objects. We compare our method to other state-of-the-art image-based rendering methods and outperform them with promising subjective and objective results on a challenging dataset.

关键词： Non-Lambetian Depth image-Based Rendering Light Field

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Nanopore Sequencing Simulator for DNA Data Storage

Nanopore Sequencing Simulator for DNA Data Storage

引用

ieee international conference on visual communications and image processing (vcip) - visual communications in the Era of AI and Limited Resources

作者： San Antonio, Eva Gil Heinis, Thomas Carteron, Louis Dimopoulou, Melpomeni Antonini, Marc Univ Cote Azur CNRS Lab I3S UMR 7271 Sophia Antipolis France Imperial Coll London Dept Comp London England

ISBN: (纸本)9781728185514

The exponential increase of digital data and the limited capacity of current storage devices have made clear the need for exploring new storage solutions. Thanks to its biological properties, DNA has proven to be a potential candidate for this task, allowing the storage of information at a high density for hundreds or even thousands of years. With the release of nanopore sequencing technologies, DNA data storage is one step closer to become a reality. Many works have proposed solutions for the simulation of this sequencing step, aiming to ease the development of algorithms addressing nanopore-sequenced reads. However, these simulators target the sequencing of complete genomes, whose characteristics differ from the ones of synthetic DNA. This work presents a nanopore sequencing simulator targeting synthetic DNA on the context of DNA data storage.

关键词： DNA data storage nanopore sequencing sequencing simulator image coding

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OBJECTIVE QUALITY ASSESSMENT FOR image RETARGETING BASED ON PERCEPTUAL DISTORTION AND INFORMATION LOSS

OBJECTIVE QUALITY ASSESSMENT FOR IMAGE RETARGETING BASED ON ...

引用

ieee international conference on visual communications and image processing (vcip)

作者： Hsu, Chih-Chung Lin, Chia-Wen Fang, Yuming Lin, Weisi School of Computer Engineering Nanyang Technological University Singapore

ISBN: (纸本)9781479902880

image retargeting techniques aim to obtain retargeted images with different sizes or aspect ratios for various display screens. Various content-aware image retargeting algorithms have been proposed recently. However, there is still no accurate objective metric for visual quality assessment of retargeted images. In this paper, we propose a novel objective metric for assessing visual quality of retargeted images based on perceptual geometric distortion and information loss. The proposed metric measures the geometric distortion of retargeted images by SIFT flow variation. Furthermore, a visual saliency map is derived to characterize human perception of the geometric distortion. On the other hand, the information loss in a retargeted image, which is calculated based on the saliency map, is integrated into the proposed metric. A user study is conducted to evaluate the performance of the proposed metric. Experimental results show the consistency between the objective assessments from the proposed metric and subjective assessments.

关键词： image Retargeting SIFT Flow Quality Assessment Quality Evaluation

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Binocular Rivalry and Fusion Mechanisms Based No-Reference Stereoscopic image Quality Assessment Considering Feedback Guidance

Binocular Rivalry and Fusion Mechanisms Based No-Reference S...

引用

2023 ieee international conference on visual communications and image processing, vcip 2023

作者： Chang, Haoxiang Li, Sumei He, Dongyue Zhang, Chen Tianjin University Tianjin China

ISBN: (纸本)9798350359855

With the growing popularity of 3D content and virtual reality applications, effective no-reference stereoscopic image quality assessment (NR-SIQA) methods have become increasingly important. In this paper, we propose a convolutional neural network (CNN) SIQA model based on binocular rivalry and fusion mechanisms of the human visual system (HVS). In order to get a better representation of binocular information, we propose Two-Stage Enhanced Fusion Module (TSEFM) that consists of two stages for monocular features enhancement and binocular features fusion, respectively. Given the dynamical characteristics of binocular rivalry phenomenon, the proposed Content-Aware Binocular Rivalry Fusion Module (CABRFM) dynamically and adaptively adjusts its output based on the input content. Additionally, considering that feedback mechanism of HVS is indispensable and significant, we introduce feedback connections during feature aggregation to realize the guidance of high-level features to low-level features. Extensive experimental results demonstrate the superiority of our method over state-of-the-art metrics, showcasing its excellent performance. © 2023 ieee.

关键词： Binoculars

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