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共 4562 条记录，以下是281-290 订阅

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GPU-Intensive Fast Entropy Coding Framework for Neural image Compression

GPU-Intensive Fast Entropy Coding Framework for Neural Image...

引用

IEEE International conference on visual communications and image processing (VCIP) - visual communications in the Era of AI and Limited Resources

作者： Akutsu, Hiroaki Naruko, Takahiro Suzuki, Akifumi Hitachi Ltd Res & Dev Grp Tokyo Japan

ISBN: (纸本)9781728185514

Neural compression has benefited from technological advances such as convolutional neural networks (CNNs) to achieve advanced bitrates, especially in image compression. In neural image compression, an encoder and a decoder can run in parallel on a GPU, so the speed is relatively fast. However, the conventional entropy coding for neural image compression requires serialized iterations in which the probability distribution is estimated by multi-layer CNNs and entropy coding is processed on a CPU. Therefore, the total compression and decompression speed is slow. We propose a fast, practical, GPU-intensive entropy coding framework that consistently executes entropy coding on a GPU through highly parallelized tensor operations, as well as an encoder, decoder, and entropy estimator with an improved network architecture. We experimentally evaluated the speed and rate-distortion performance of the proposed framework and found that we could significantly increase the speed while maintaining the bitrate advantage of neural image compression.

关键词： neural image compression entropy coding GPU

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Underwater image Enhancement with Multi-Scale Residual Attention Network

Underwater Image Enhancement with Multi-Scale Residual Atten...

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IEEE International conference on visual communications and image processing (VCIP) - visual communications in the Era of AI and Limited Resources

作者： Ueki, Yosuke Ikehara, Masaaki Keio Univ EEE Dept Yokohama Kanagawa 2238522 Japan

ISBN: (纸本)9781728185514

Underwater images suffer from low contrast, color distortion and visibility degradation due to the light scattering and attenuation. Over the past few years, the importance of underwater image enhancement has increased because of ocean engineering and underwater robotics. Existing underwater image enhancement methods are based on various assumptions. However, it is almost impossible to define appropriate assumptions for underwater images due to the diversity of underwater images. Therefore, they are only effective for specific types of underwater images. Recently, underwater image enhancement algorisms using CNNs and GANS have been proposed, but they are not as advanced as other image processing methods due to the lack of suitable training data sets and the complexity of the issues. To solve the problems, we propose a novel underwater image enhancement method which combines the residual feature attention block and novel combination of multi-scale and multi-patch structure. Multi-patch network extracts local features to adjust to various underwater images which are often Non-homogeneous. In addition, our network includes multi-scale network which is often effective for image restoration. Experimental results show that our proposed method outperforms the conventional method for various types of images.

关键词： image processing image enhancement image restoration underwater image attention

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Perceptual Evaluation of Pre-processing for Video Transcoding

Perceptual Evaluation of Pre-processing for Video Transcodin...

引用

IEEE International conference on visual communications and image processing (VCIP) - visual communications in the Era of AI and Limited Resources

作者： Huang, Shiyu Luo, Ziyuan Xu, Jiahua Zhou, Wei Chen, Zhibo Univ Sci & Technol China CAS Key Lab Technol Geospatial Informat Proc & Ap Hefei Peoples R China

ISBN: (纸本)9781728185514

Recently, the pre-processed video transcoding has attracted wide attention and has been increasingly used in practical applications for improving the perceptual experience and saving transmission resources. However, very few works have been conducted to evaluate the performance of pre-processing methods. In this paper, we select the source (SRC) videos and various pre-processing approaches to construct the first Pre-processed and Transcoded Video Database (PTVD). Then, we conduct the subjective experiment, showing that compared with the video sent to the codec directly at the same bitrate, the appropriate pre-processing methods indeed improve the perceptual quality. Finally, existing image/video quality metrics are evaluated on our database. The results indicate that the performance of the existing image/video quality assessment (IQA/VQA) approaches remain to be improved. We will make our database publicly available soon.

关键词： Video quality assessment Subjective evaluation Database Pre-processing for video transcoding

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No-Reference Stereoscopic image Quality Assessment Considering Binocular Disparity and Fusion Compensation

No-Reference Stereoscopic Image Quality Assessment Consideri...

引用

IEEE International conference on visual communications and image processing (VCIP) - visual communications in the Era of AI and Limited Resources

作者： Feng Jinhui Li, Sumei Chang, Yongli Tianjin Univ Tianjin Int Engn Inst Tianjin Peoples R China Tianjin Univ Sch Elect & Informat Engn Tianjin Peoples R China

ISBN: (纸本)9781728185514

In this paper, we propose an optimized dual stream convolutional neural network (CNN) considering binocular disparity and fusion compensation for no-reference stereoscopic image quality assessment (SIQA). Different from previous methods, we extract both disparity and fusion features from multiple levels to simulate hierarchical processing of the stereoscopic images in human brain. Given that the ocular dominance plays an important role in quality evaluation, the fusion weights assignment module (FWAM) is proposed to assign weight to guide the fusion of the left and the right features respectively. Experimental results on four public stereoscopic image databases show that the proposed method is superior to the state-of-the-art SIQA methods on both symmetrical and asymmetrical distortion stereoscopic images.

关键词： stereoscopic image quality assessment dual stream ocular dominance binocular disparity binocular fusion

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Deformable Convolution Based No-Reference Stereoscopic image Quality Assessment Considering visual Feedback Mechanism

Deformable Convolution Based No-Reference Stereoscopic Image...

引用

IEEE International conference on visual communications and image processing (VCIP) - visual communications in the Era of AI and Limited Resources

作者： Zhou, Mingyue Li, Sumei Tianjin Univ Sch Elect & Informat Engn Tianjin Peoples R China

ISBN: (纸本)9781728185514

Simulation of human visual system (HVS) is very crucial for fitting human perception and improving assessment performance in stereoscopic image quality assessment (SIQA). In this paper, a no-reference SIQA method considering feedback mechanism and orientation selectivity of HVS is proposed. In HVS, feedback connections are indispensable during the process of human perception, which has not been studied in the existing SIQA models. Therefore, we design a new feedback module (FBM) to realize the guidance of the high-level region of visual cortex to the low-level region. In addition, given the orientation selectivity of primary visual cortex cells, a deformable feature extraction block is explored to simulate it, and the block can adaptively select the regions of interest. Meanwhile, retinal ganglion cells (RGCs) with different receptive fields have different sensitivities to objects of different sizes in the image. So a new multi receptive fields information extraction and fusion manner is realized in the network structure. Experimental results show that the proposed model is superior to the state-of-the-art no-reference SIQA methods and has excellent generalization ability.

关键词： stereoscopic image quality assessment (SIQA) human visual system (HVS) feedback mechanism deformable convolution

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MPEG Immersive Video tools for Light Field Head Mounted Displays

MPEG Immersive Video tools for Light Field Head Mounted Disp...

引用

IEEE International conference on visual communications and image processing (VCIP) - visual communications in the Era of AI and Limited Resources

作者： Bonatto, Daniele Hirt, Gregoire Kvasov, Alexander Fachada, Sarah Lafruit, Gauthier Univ Libre Bruxelles Labs Image Synth & Anal Brussels Belgium CREAL Lausanne Switzerland Fonds Rech Sci FNRS Brussels Belgium

ISBN: (纸本)9781728185514

Light field displays project hundreds of microparallax views for users to perceive 3D without wearing glasses. It results in gigantic bandwidth requirements if all views would be transmitted, even using conventional video compression per view. MPEG Immersive Video (MIV) follows a smarter strategy by transmitting only key images and some metadata to synthesize all the missing views. We developed (and will demonstrate) a real-time Depth image Based Rendering software that follows this approach for synthesizing all light field micro-parallax views from a couple of RGBD input views.

关键词： Demo View Synthesis DIBR Holography

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TSANet: Two-subnet Attention Network for Single image Dehazing 14

TSANet: Two-subnet Attention Network for Single Image Dehazi...

引用

14th IEEE International conference on Wireless communications and Signal processing (WCSP)

作者： Jiang, Chenran Yan, Fei Deng, Tao Sun, Lin Li, Jun Southwest Jiaotong Univ Sch Informat Sci & Technol Chengdu Peoples R China China Elect Product Reliabil & Environm Testing R Guangzhou Peoples R China

ISBN: (纸本)9781665450850

Haze restricts visual quality and degrades the quality of captured images. The aim of single image dehazing is to recover a haze-free image from a hazy one. However, most present image dehazing methods treat different feature information in channels and pixels evenly, which may influence the dehazing result because of the uneven distribution of haze. To address hazy uneven distribution, we propose an end-to-end two-subnet attention network (TSANet), which consists of attention-recurrent (AR) and asymmetric u-shaped dehazing refinement (AUDR). In addition, a feature residual attention (FRA) block is designed to focus on thick-hazy regions and high-frequency regions of a hazy image when dehazing. In the model, the input image is first fed into the AR sub-network to extract feature information like thick hazy regions and high-frequency regions. For further feature refinement, we propose the AUDR sub-network to further process feature information from the AR sub-network. The AUDR sub-network adopts an encoder-decoder module containing FRA and transformer blocks to further process feature information of high-frequency regions and filter hazy feature information, and uses skip connections to enhance the representation of our TSANet. The extensive experimental results demonstrate the effectiveness of our method and outperform other dehazing methods on synthetic and real-world hazy datasets.

关键词： Single image dehazing feature residual attention attention-recurrent asymmetric u-shaped dehazing refinement

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The Research on the Impact of visual image Perception in a User Interface on Typeface Design 5

The Research on the Impact of Visual Image Perception in a U...

引用

5th International conference on Imaging, Signal processing and communications (ICISPC)

作者： Cao, Yang Hunan Normal Univ Fine Arts Acad Changsha Peoples R China

ISBN: (纸本)9781665424257

Nowadays, Typeface plays an increasingly important role in dynamic digital interfaces, but there still has little direct evaluation of visual image perception related to the typeface design, especially for the use in interface typography. The research is based on the analysis of display screen, elaborates upon the connection between display resolution and typeface design, the relationship between display polarity and the principle of vision optics. Furthermore, essential attributes and requirements of the two genre of interface font are inspected from the human visual image perception. Additionally, the visual processing of text information and visual characteristics in scanning state are elaborated, visual Angle and spatial frequency of visual perception are identified as the cornerstones influencing the design of a typeface for user interface. The methodology of visual perception can be adapted to investigate questions relevant to typographic and typeface design.

关键词： image visual perception interface typeface design

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Towards Universal GAN image Detection

Towards Universal GAN Image Detection

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IEEE International conference on visual communications and image processing (VCIP) - visual communications in the Era of AI and Limited Resources

作者： Cozzolino, Davide Gragnaniello, Diego Poggi, Giovanni Verdoliva, Luisa Univ Federico II Naples Naples Italy

ISBN: (纸本)9781728185514

The ever higher quality and wide diffusion of fake images have spawn a quest for reliable forensic tools. Many GAN image detectors have been proposed, recently. In real world scenarios, however, most of them show limited robustness and generalization ability. Moreover, they often rely on side information not available at test time, that is, they are not universal. We investigate these problems and propose a new GAN image detector based on a limited sub-sampling architecture and a suitable contrastive learning paradigm. Experiments carried out in challenging conditions prove the proposed method to be a first step towards universal GAN image detection, ensuring also good robustness to common image impairments, and good generalization to unseen architectures.

关键词： Fake detection

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Inter-Observer visual Congruency in Video-Viewing

Inter-Observer Visual Congruency in Video-Viewing

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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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