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检索条件"任意字段=Conference on Visual Communications and Image Processing"

共 3469 条记录，以下是101-110 订阅

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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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Fully Aligned Network for Referring image Segmentation

Fully Aligned Network for Referring Image Segmentation

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2024 conference on visual communications and image processing

作者： Liu, Yong Xu, Ruihao Tang, Yansong Tsinghua Univ Tsinghua Shenzhen Int Grad Sch Shenzhen Peoples R China

ISBN: (纸本)9798331529543;9798331529550

This paper focuses on the Referring image Segmentation (RIS) task, which aims to segment objects from an image based on a given language description, having significant potential in practical applications such as food safety detection. Recent advances using the attention mechanism for cross-modal interaction have achieved excellent progress. However, current methods tend to lack explicit principles of interaction design as guidelines, leading to inadequate cross-modal comprehension. Additionally, most previous works use a single-modal mask decoder for prediction, losing the advantage of full cross-modal alignment. To address these challenges, we present a Fully Aligned Network (FAN) that follows four cross-modal interaction principles. Under the guidance of reasonable rules, our FAN achieves state-of-the-art performance on the prevalent RIS benchmarks (RefCOCO, RefCOCO+, G-Ref) with a simple architecture.

关键词： image segmentation

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Adaptive Threshold-based Sparse Representation Network for image Compressive Sensing Reconstruction

Adaptive Threshold-based Sparse Representation Network for I...

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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： Xuan, Yunyi Yang, Chunling Yang, Xin South China Univ Technol Sch Elect & Informat Engn Guangzhou Peoples R China

ISBN: (纸本)9781728185514

Recently, network-based image Compressive Sensing (ICS) algorithms show superior performance in reconstruction quality and speed, yet non-interpretable. Herein, we propose an Adaptive Threshold-based Sparse Representation Reconstruction Network (ATSR-Net), composed of the Convolutional Sparse Representation subnet (CSR-subnet) and the truly Adaptive Threshold Generation subnet (ATG-subnet). The traditional iterations are unfolded into several CSR-subnets, which can fully exploit the local and nonlocal similarities. The ATG-subnet automatically determines a threshold map based on the image intrinsic characterization for flexible feature selection. Moreover, we present a three-level consistency loss based on pixel-level, measurement-level, and feature-level, to accelerate the network convergence. Extensive experiment results demonstrate the superiority of the proposed network to the existing state-of-the-art methods by large margins, both quantitatively and qualitatively.

关键词： image compressive sensing sparse representation adaptive threshold generation

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Video Compression based on Jointly Learned Down-Sampling and Super-Resolution Networks

Video Compression based on Jointly Learned Down-Sampling and...

引用

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

作者： Wei, Yuzhuo Chen, Li Song, Li Shanghai Jiao Tong Univ Inst Image Commun & Network Engn Shanghai Peoples R China

ISBN: (纸本)9781728185514

With the blooming of deep learning technology in computer vision, the integration of deep learning and the traditional video coding has made significant improvements, especially applying the super-resolution neural network as the post-processing module in the down-sampling-based video compression framework. However, the pre-processing module lacks back-propagated gradients for jointly considering down-sampling and up-sampling due to the non-differentiability of the traditional video codec. In this paper, we propose an end-to-end down-sampling-based video compression framework applying convolutional neural networks both as down-sampling and up-sampling. We use a virtual codec neural network to approximate the actual video codec so that the gradient can be effectively back-propagated for joint training. Experimental results show the superiority of our proposed framework compared with the predefined down-sampling-based video compression and various methods of joint training.

关键词： super-resolution video compression deep learning

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Polynomial image-Based Rendering for non-Lambertian Objects

Polynomial Image-Based Rendering for non-Lambertian Objects

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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： 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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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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Nearly Reversible image-to-image Translation Using Joint Inter-Frame Coding and Embedding

Nearly Reversible Image-to-Image Translation Using Joint Int...

引用

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

作者： Cao, Xinzhu Yao, Yuanzhi Yu, Nenghai Univ Sci & Technol China Dept Elect Engn & Informat Sci Hefei 230027 Peoples R China

ISBN: (纸本)9781728185514

image-to-image translation tasks which have been widely investigated with generative adversarial networks (GAN) aim to map an image from the source domain to the target domain. The translated image can be inversely mapped to the reconstructed source image. However, existing GAN-based schemes lack the ability to accomplish reversible translation. To remedy this drawback, a nearly reversible image-to-image translation scheme where the reconstructed source image is approximately distortion-free compared with the corresponding source image is proposed in this paper. The proposed scheme jointly considers inter-frame coding and embedding. Firstly, we organize the GAN-generated reconstructed source image and the source image into a pseudo video. Furthermore, the bitstream obtained by inter-frame coding is reversibly embedded in the translated image for nearly lossless source image reconstruction. Extensive experimental results and analysis demonstrate that the proposed scheme can achieve a high level of performance in image quality and security.

关键词： image-to-image translation generative adversarial network inter-frame coding reversible data embedding

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An Error Self-learning Semi-supervised Method for No-reference image Quality Assessment

An Error Self-learning Semi-supervised Method for No-referen...

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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： Feng, Yingjie Li, Sumei Hao, Sihan Tianjin Univ Sch Elect & Informat Engn Tianjin Peoples R China

ISBN: (纸本)9781728185514

In recent years, deep learning has achieved significant progress in many respects. However, unlike other research fields with millions of labeled data such as image recognition, only several thousand labeled images are available in image quality assessment (IQA) field for deep learning, which heavily hinders the development and application for IQA. To tackle this problem, in this paper, we proposed an error self-learning semi-supervised method for no-reference (NR) IQA (ESSIQA), which is based on deep learning. We employed an advanced full reference (FR) IQA method to expand databases and supervise the training of network. In addition, the network outputs of expanding images were used as proxy labels replacing errors between subjective scores and objective scores to achieve error self-learning. Two weights of error back propagation were designed to reduce the impact of inaccurate outputs. The experimental results show that the proposed method yielded comparative effect.

关键词： error self-learning semi-supervised no-reference image quality assessment

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MSCI: A Multi-Source Composite image Database for Compression Distortion Quality Assessment

MSCI: A Multi-Source Composite Image Database for Compressio...

引用

IEEE International conference on visual communications and image processing (VCIP)

作者： Zhang, Xiaofang Xu, Zhuowei Lin, Zhiheng Wang, Miaohui Shenzhen Univ Coll Informat & Elect Engn Shenzhen Peoples R China Jimei Univ Coll Marine Equipment & Mech Engn Xiamen Peoples R China

ISBN: (纸本)9781665475921

With the rapid development of multi-sensor fusion technology in various industrial fields, many composite images closely related to human life have been produced. To meet the rapidly growing needs of various image-based applications, we have established the first multi-source composite image (MSCI) database for image quality assessment (IQA). Our MSCI database contains 80 reference images and 1600 distorted images, generated by four advanced compression standards with five distortion levels. In particular, these five distortion levels are determined based on the first five just noticeable difference (JND) levels. Moreover, we verify the IQA performance of some representative methods on our MSCI database. The experimental results show that the performance of the existing methods on the MSCI database needs to be further improved.

关键词： image quality assessment multi-sensor composite image compression distortion

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Fast and Context-Aware Framework for Space-Time Video Super-Resolution

Fast and Context-Aware Framework for Space-Time Video Super-...

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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： Zhang, Xueheng Chen, Li Song, Li Gao, Zhiyong Shanghai Jiao Tong Univ Inst Image Commun & Network Engn Shanghai Peoples R China

ISBN: (纸本)9781728185514

Increasing the spatial resolution and frame rate of a video simultaneously has attracted attention in recent years. The current one-stage space-time video super-resolution (STVSR) methods are difficult to deal with large motion and complex scenes, and are time-consuming and memory intensive. We propose an efficient STVSR framework, which can correctly handle complicated scenes such as occlusion and large motion and generate results with clearer texture. In REDS dataset, our method outperforms all existing one-stage methods. Our method is lightweight and can generate 720p frames at 16fps on a NVIDIA GTX 1080 Ti GPU.

关键词： space-time video super-resolution frame interpolation deep learning

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