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Face image Inpainting Using Context Encoders and Dynamically Initialized Mask 1

引用

8th International conference on Computer Vision and image processing (CVIP)

作者： Maurya, Sahil Sandhan, Tushar Indian Inst Technol Dept EE Percept & Intelligence Lab Kanpur Uttar Pradesh India

ISBN: (数字)9783031585357

ISBN: (纸本)9783031585340;9783031585357

The problem of recovering missing data has garnered considerable attention due to its significance and challenges in recent times. In particular, the ability to recover clear face images from occluded face images has found applications in various domains. One prominent approach in this context is the utilization of autoencoders within the framework of Generative Adversarial Networks (GAN), such as the Context Encoder (CE). The CE is an unsupervised algorithm that leverages an autoencoder as its generator. It is designed to inpaint missing areas in an image based on the information present in the surrounding areas. By learning a compressed representation of the input image, the autoencoder can generate plausible and visually coherent predictions for the missing regions. We found that the initial values of the pixels in the missing area have a significant effect on the quality of the generated images. Careful selection of these initial values proved crucial in achieving accurate and visually appealing inpainted results. Furthermore, we explored various useful loss functions that can be employed within the model. We discovered that the choice of loss function also has a substantial effect on the visual quality of the generated images.

关键词： Generative Adversarial Networks Autoencoders Context encoders Inpainting Face images

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End-to-end image Compression with Swin-Transformer

End-to-end Image Compression with Swin-Transformer

引用

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

作者： Wang, Meng Zhang, Kai Zhang, Li Li, Yue Li, Junru Wang, Yue Wang, Shiqi City Univ Hong Kong Dept Comp Sci Hong Kong Peoples R China Bytedance Inc San Diego CA 92122 USA Beijing Bytedance Technol Co Ltd Beijing Peoples R China

ISBN: (纸本)9781665475921

In this paper, we propose an end-to-end image compression framework, which cooperates with the swin-transformer modules to capture the localized and non-localized similarities in image compression. In particular, the swin-transformer modules are deployed in the analysis and synthesis stages, interleaving with convolution layers. The transformer layers are expected to perceive more flexible receptive fields, such that the spatially localized and non-localized redundancies could be more effectively eliminated. The proposed method reveals the excellent capability of signal conjunction and prediction, leading to the improvement of the rate and distortion performance. Experimental results show that the proposed method is superior to the existing methods on both natural scene and screen content images, where 22.46% BD-Rate savings are achieved when compared with the BPG. Over 30% BD-Rate gains could be observed with screen content images when compared with the classical hyper-prior end-to-end coding method.

关键词： image compression end-to-end compression transformer convolution

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An Integrated Model for Generating 3D Point Clouds and Segmentation from 2D images 8

An Integrated Model for Generating 3D Point Clouds and Segme...

引用

8th International conference on Imaging, Signal processing and communications (ICISPC)

作者： Chen, Huan-Yu Lin, Chuen-Horng Lin, Yan-Yu Chan, Yung-Kuan Natl Taichung Univ Sci & Technol Dept Comp Sci & Informat Engn 129 Sec 3Sanmin Rd Taichung Taiwan Natl Chung Hsing Univ Dept Management Informat Syst 145 Xingda Rd Taichung 402 Taiwan

ISBN: (纸本)9798350367164;9798350367157

This study presents a cost-effective approach to constructing simulation systems by integrating 2D visual processing with neural network technology for simultaneous 3D point cloud generation and part segmentation, thereby reducing time and costs. We propose multiple task-specific models using 2D RGB images, incorporating attention mechanisms, feature encoding, decoding layers, and innovative loss functions. The optimal models are merged to form an integrated system, evaluated using public and self-built datasets. Our experiments demonstrate that the integrated model effectively reduces training time and Floating Point Operations (FLOP) values while maintaining high accuracy in Critical Hole Distance (CHD), Earth Mover's Distance (EMD), and Intersection over Union (IOU) metrics. This advancement enhances applications in military training, aerospace technology, and disaster response simulation, facilitating faster 3D object construction.

关键词： Deep learning 2D image point cloud integrated learning reconstruction part segmentation

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Adaptive Entropy Coding of Graph Transform Coefficients for Point Cloud Attribute Compression

Adaptive Entropy Coding of Graph Transform Coefficients for ...

引用

2023 IEEE International conference on visual communications and image processing, VCIP 2023

作者： Meyer, Thibaut Mehlem, Dominik Rohlfing, Christian RWTH Aachen University Institut für Nachrichtentechnik Germany

ISBN: (纸本)9798350359855

A point cloud's attributes constitutes most of its information content. This is why their efficient compression is of great importance when designing a compression scheme. In this paper, the entropy coding stage of an existing compression method is replaced using Context-based Adaptive Binary Arithmetic Coding (CABAC), which is already largely used for video compression applications. Additionally, the DC transform coefficients are quantized with Differential Pulse Code Modulation (DPCM), yielding better performance at lower bit rates. By using predictive coding and coding techniques adapted to the signal's characteristics, Bjontegaard Delta rate savings of up to 31.38% are observable in comparison to previously used entropy coding methods. © 2023 IEEE.

关键词： image compression

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3D Tensor Display for Non-Lambertian Content

3D Tensor Display for Non-Lambertian Content

引用

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

作者： Losfeld, Armand Soetens, Eline Bonatto, Daniele Fachada, Sarah Van Bogaert, Laurie Lafruit, Gauthier Teratani, Mehrdad Univ Libre Bruxelles Lab Image Synth & Anal Brussels Belgium

ISBN: (纸本)9781665475921

A tensor display is a type of 3D light field display, composed of multiple transparent screens and a back-light that can render a scene with correct depth, allowing to view a 3D scene without wearing glasses. The analysis of state-of-the-art tensor displays assumes that the content is Lambertian. In order to extend its capabilities, we analyze the limitations of displaying non-Lambertian scenes and propose a new method to factorize the non-Lambertian scenes using disparity analysis. Moreover, we demonstrate a new prototype of a tensor display with three layers of full HD content at 60 fps. Compared with state-of-the-art, the evaluation results verify that the proposed non-Lambertian rendering method can display a higher quality for non-Lambertian scenes on both simulation and a prototyped tensor display.

关键词： Non-Lambertian prototype tensor display depth range disparity range simulation light field

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STVP: A Spatiotemporal visual Perception Method for User-generated Content Video Quality Assessment

STVP: A Spatiotemporal Visual Perception Method for User-gen...

引用

2023 IEEE International conference on visual communications and image processing, VCIP 2023

作者： Ai, Da Lu, Mingyue Wang, Jiahao Liu, Ying Xi'An University of Posts and Telecommunications Center for Image and Information Processing Xi'an China Xi'An University of Posts and Telecommunications School of Communication and Information Engineering Xi'an China

ISBN: (纸本)9798350359855

With the popularity and development of short video applications, the behavior of using mobile devices to shoot and share user-generated content (UGC) videos has become increasingly common. Video quality assessment (VQA) is critical in guaranteeing end-user viewing experiences. UGC-VQA is a challenging problem due to the complexity and variety of distortion types of UGC videos and the absence of reference videos. To improve the consistency of UGC-VQA results and human subjective ratings, in this paper, we propose a UGC-VQA method based on spatiotemporal visual perception (STVP). Firstly, a hierarchical feature fusion module was added to the feature extraction network to realize the fusion of low-level visual features and high-level semantic features, and obtain the quality perception features with rich visual information. Then, we use the self-Attention to weight different frames to distinguish their importance. The long short-Term memory (LSTM) network and the time pool are used to model long-Term dependencies and temporal memory effects. Experimental results on UGC-VQA datasets show that the proposed method achieves a performance improvement of nearly 2%, and its evaluation results are more consistent with human visual perception. © 2023 IEEE.

关键词： Semantics

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Single image Super-Resolution Using ConvNeXt

Single Image Super-Resolution Using ConvNeXt

引用

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

作者： You, Chenghui Hong, Chaoqun Liu, Lijuan Lin, Xuehan Xiamen Univ Technol Sch Comp & Informat Engn Xiamen Peoples R China

ISBN: (纸本)9781665475921

In recent years, a lot of deep convolution neural networks have been successfully applied in single image super-resolution (SISR). Even in the case of using small convolution kernel, those methods still require large number of parameters and computation. To tackle the problem above, we propose a novel framework to extract features more efficiently. Inspired by the idea of deep separable convolution, we improve the standard residual block and propose the inverted bottleneck block (IBNB). The IBNB replaces the small-sized convolution kernel with the large-sized convolution kernel without introducing additional computation. The proposed IBNB proves that large kernel size convolution is available for SISR. Comprehensive experiments demonstrate that our method surpasses most methods by up to 0.10 similar to 0.32dB in quantitative metrics with fewer parameters.

关键词： single image super-resolution convolutional neural network deep separable convolution

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Context-Aware Seam Restoration for image Extension

Context-Aware Seam Restoration for Image Extension

引用

2023 IEEE International conference on visual communications and image processing, VCIP 2023

作者： Heo, Yuk Koh, Yeong Jun Kim, Chang-Su Korea University Seoul Korea Republic of Chungnam National University Daejeon Korea Republic of

ISBN: (纸本)9798350359855

A seam is a set of pixels with minimum energy forming a continuous line in an image. By eliminating or duplicating seams iteratively, an input image can be retargeted. However, this process often results in blurring, stretching, or distortion problems around the seams, especially when extending a target image. We propose a novel approach for image extension using content-Aware seam restoration to solve this problem. First, we design CSR-Net, which employs features from the horizontal region of target pixels to restore the seams. Second, we develop an image extension scenario based on the seam restoration and the training methodology of CSR-Net. Experimental results demonstrate that the proposed algorithm provides more accurate expanded results at seam pixels the seams than conventional algorithms. © 2023 IEEE.

关键词： Restoration

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Multi-View image Rectification for UAV-Captured image Sequences

Multi-View Image Rectification for UAV-Captured Image Sequen...

引用

2023 IEEE International conference on visual communications and image processing, VCIP 2023

作者： Zou, Shun Jin, Xin Fan, Yihui Tsinghua University Shenzhen International Graduate School Shenzhen China

ISBN: (纸本)9798350359855

The image sequences captured by Unmanned Aerial Vehicles (UAVs) can be applied to many computer vision tasks. However, due to the instability of UAV flight, the captured image sequences will deviate from the preset trajectory and pose, which reduce the quality of subsequent applications such as panoramic image stitching. In this paper, a novel method is proposed to rectify UAV-captured image sequences by transforming the images to a regular trajectory with the uniform pose. First, to minimize the total transformation deviation, virtual regular camera trajectory is derived by minimizing the global error of coordinates between actual and virtual camera trajectories. Then, camera-pose-relevant local homography is proposed by inserting the camera pose into local homography to transform the images to the derived virtual trajectory with the uniform pose and correct translation parallax. The experimental results demonstrate the effectiveness of the proposed rectification algorithm from both theoretical and application levels. © 2023 IEEE.

关键词： Cameras

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Coding of Multi-Focused Plenoptic image using Disparity Shift and Sharpness-Aware Constraints

Coding of Multi-Focused Plenoptic Image using Disparity Shif...

引用

2023 IEEE International conference on visual communications and image processing, VCIP 2023

作者： Huu, Thuc Nguyen Van Duong, Vinh Yim, Jonghoon Jeon, Byeungwoo Sungkyunkwan University Dept. of Electrical and Computer Engineering Korea Republic of

ISBN: (纸本)9798350359855

Multi-focused plenoptic images possess many special characteristics related to the micro-images (MIs) array, which are expected to be useful in further increasing its compression performance. Those special characteristics come from the much overlap and sharpness variance among its micro-images, and proper handling of such properties can lead to better patch-based prediction. In this paper, for multi-focused plenoptic image data, we design a new prediction model taking into account the disparity shift constraint coming from the overlaps and the sharpness variation. Experiment results show coding gain respectively of 21% over the HEVC Intra and 27% when the proposed method is combined with the Intra Block Copy (IBC) tool which is reported very effective in plenoptic image coding. © 2023 IEEE.

关键词： image coding

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