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检索条件"机构=The Key Laboratory of Image Understanding and Computer Vision"

共 314 条记录，以下是91-100 订阅

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Multi-Task Learning with Deep Dual-Path Network for Facial Attribute Recognition 2020

Multi-Task Learning with Deep Dual-Path Network for Facial A...

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Proceedings of the 2020 9th International Conference on Computing and Pattern Recognition

作者： Xinyu Lai Si Chen Da-Han Wang Shunzhi Zhu School of Computer and Information Engineering Xiamen University of Technology Fujian Key Laboratory of Pattern Recognition and Image Understanding School of Computer and Information Engineering Xiamen University of Technology Fujian Key Laboratory of Pattern Recognition and Image Understanding

ISBN: (纸本)9781450387835

Facial attribute recognition is a popular and challenging research topic in computer vision. In the traditional deep learning based attribute recognition methods, the mid-level network features and the differences between attribute groups are not fully explored. To solve the above problem, a deep dual-path network is proposed for facial attribute recognition. In the multi-task learning framework, two sub-networks are employed to respectively extract the features of two attribute groups, i.e., local attributes and global ones, and designed with both different scale images and different depth networks. Furthermore, an adaptive Focal loss penalty scheme is developed to automatically assign weights to handle the class imbalance problem for facial attribute recognition. Experimental results on the challenging CelebA dataset show that the proposed method achieves the better performance than state-of-the-art methods.

关键词： multi-task learning dual-path network Facial attribute recognition attribute groups

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Stereo matching algorithm based on the combination of matching costs 7

Stereo matching algorithm based on the combination of matchi...

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7th IEEE Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2017

作者： Ende, Wang Yalong, Zhu Liangyu, Peng Yijun, Li Tianyao, Wu Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Opto-Electronic Information Processing CAS Shenyang110016 China Key Lab of Image Understanding and Computer Vision Liaoning Province Shenyang110016 China College of Electrical Engineering Yanshan University Qinhuangdao066004 China School of Metallurgy Northeastern University Shenyang110819 China

ISBN: (纸本)9781538604892

Aiming at solving the problem of low accuracy of weak texture region and disparity discontinuous region and sensitivity to illumination caused by existing local stereo matching algorithm, a new stereo matching algorithm based on the combination of Sum of Absolute Difference algorithm and Absolute Difference of Gradient algorithm is presented here. Using the average of the pixels in the disparity range to apply adaptive weight to the SAD part. The new algorithm can adaptively adjust each part of the cost function in the proportion of the total cost function according to the different texture, illumination characteristics of image. Moreover, we use the semiglobal matching algorithm to calculate the cost of 8 directions, to carry out optimized processing on disparity image, finally a dense disparity map is obtained. The experimental results shows that the proposed method not only improve accuracy of stereo matching, but also has well results in weak texture region and disparity discontinuous region. © 2017 IEEE.

关键词： Textures

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An improved SSD for small target detection 2021

An improved SSD for small target detection

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6th International Conference on Multimedia and image Processing, ICMIP 2021

作者： Li, Xiang Luo, Haibo Key Laboratory of Opt-Electronic Information Processing Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China The Key Laboratory of Image Understanding and Computer Vision Shenyang Liaoning110016 China

ISBN: (纸本)9781450389167

SSD is one of heuristic one-stage target detection approaches. Although it has got impressive results in general target detection, it still struggles in small-size object detection and precise location. In this paper, we proposed an improved SSD which forces on the small-size target detection. We include a shallow and high resolution feature into the hierarchical detection feature which are used for prediction. Then, we fuse the detection features (including the shallow and high resolution one) as a feature pyramid through some convolution layers and unsample operations to pass information from deep features to the shallow ones, aiming to enrich the semantic information of the shallow features. To make the network easier to converge, we add a L2 normalization to the bottom detection feature of the feature pyramid to make a norm balance between each pyramid feature. The experimental results on the VEDAI dataset show that the proposed method has obtained impressive progress than the original SSD for the small targets detection. © 2021 ACM.

关键词： Object detection

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image saliency detection method based on multi-feature maps fusion 4

Image saliency detection method based on multi-feature maps ...

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4th International Conference on computer Graphics, image, and Virtualization, ICCGIV 2024

作者： Li, Xiaoli Liu, Yunpeng Zhao, Huaici Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Key Laboratory of Opto-Electronic Information Processing Shenyang China The Key Lab of Image Understanding and Computer Vision Shenyang China Shenyang Jianzhu University Shenyang China

ISBN: (纸本)9781510683242

In this research, we introduce an innovative saliency detection algorithm, comprising three essential steps. Firstly, leveraging fully convolutional networks with aggregation interaction modules, we generate an initial saliency map. Secondly, we extract hand-craft and deep features to express the image, then use manifold ranking method to construct saliency maps. Ultimately, by integrating the outcomes from preceding stages, we generate the final saliency map. Experimental findings demonstrate that our method surpasses twelve cutting-edge saliency detection techniques in terms of precision, recall, F-measure, and MAE value metrics." © 2024 SPIE.

关键词： Feature extraction

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Unsupervised Terahertz image Restoration Based on CycleGan 3

Unsupervised Terahertz Image Restoration Based on CycleGan

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3rd International Conference on Defence Technology, ICDT 2022

作者： Su, Zhipeng Zhang, Yixiong Qi, Feng Shi, Jianghong School of Informatics Xiamen University National Demonstrative Software School Xiamen361005 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Opto-Electronic Information Process Shenyang110016 China Key Laboratory of Image Understanding and Computer Vision Shenyang110016 China

Terahertz (THz) is considered as one of the key technologies for sixth generation communications, military, medical imaging and industrial inspection. THz images are susceptible to degradation due to system noise and point spread functions during transmission. The existing deep learning methods use ground truth and input images for supervised training that can recover THz images very well. But it's difficult to obtain labeled THz data in practical application. In this paper, we propose an attentional adversarial cycle generation network for THz image restoration (CycleTHz) based on CycleGan to address this problem. The CycleTHz generates clean images firstly by an attention-guided generation network and then discriminates the quality of the generators by an attention discriminator. In addition, RGB color loss is used for image channels for constraint. To the best of our knowledge, this is the first THz dataset to be trained using an unsupervised approach. Extensive experiments show that the proposed method improves the PSNR and SSIM by 43.4% and 101.7% compared with CycleGan, which is a benchmark method for the unsupervised development in THz image restoration. The code is available at https://***/hellogry/UnsupervisedCycleTHz © Published under licence by IOP Publishing Ltd.

关键词： image reconstruction

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An Improved Real-time Visual Tracking Method for Space Non-cooperate Target

An Improved Real-time Visual Tracking Method for Space Non-c...

引用

International Symposium on Optoelectronic Technology and Application 2016(OTA 2016)——Conf.6 Robot Sensing and Advanced Control

作者： Limin Zhang Feng Zhu Yingming Hao Shenyang institute of automation Chinese academy of sciences University of Chinese Academy of Sciences Key laboratory of optical-electronics information processing Chinese academy of science Key laboratory of image understanding and computer vision

In order to enable the non-cooperative rendezvous, capture, and removal of large space debris, robust and fast tracking of the non-cooperative target is needed. This paper proposes an algorithm of rea

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Shape Matching under Affine Transformation Using Normalization and Multi-scale Area Integral Features

Shape Matching under Affine Transformation Using Normalizati...

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International Symposium on Optoelectronic Technology and Application 2016(OTA 2016)——Conf.6 Robot Sensing and Advanced Control

作者： Huiying Cai Feng Zhu Yingming Hao Rongrong Lu Shenyang institute of automation Chinese academy of sciences University of Chinese Academy of Sciences Key laboratory of optical-electronics information processing Chinese academy of science Key laboratory of image understanding and computer vision

Shape refers to the equivalence representation of objects obtained through projecting the objects onto the imaging planes. The projecting action can be fitted by some finite-dimensional transformation

ISBN: (纸本)9781510607729

关键词： Shape matching Orthogonal normalization Equivalent resample Multi-scale area integral features Affine transformation Area integral shape analysis edge pixel Shape normalization multi-scale

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image Restoration for Terahertz image Based on Complex-Valued Deconvolution 8

Image Restoration for Terahertz Image Based on Complex-Value...

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8th Asia-Pacific Conference on Antennas and Propagation, APCAP 2019

作者： Ning, Wei Qi, Feng Wang, Jinkuan Northeastern University School of Computer Science and Engineering Shenyang110169 China Chinese Academy of Sciences Shenyang Institute of Automation Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Opto-Electronic Information Processing Chinese Academy of Sciences Shenyang110016 China Key Lab of Image Understanding and Computer Vision Liaoning Province Shenyang110016 China

ISBN: (纸本)9781665400541

According to the unique characteristics of terahertz (THz) waves, THz imaging has become a hot topic in widely application areas. However, the imaging resolution is constrained by its long wavelength. Generally, the deconvolution is always used to reconstruct the object function. In this paper, a method that combining the classic deconvolution algorithm with the complex-value data processing is investigated. It is posed that the proposed complex-number deconvolution achieves better performance compared to the real-valued deconvolution. © 2019 IEEE.

关键词： Deconvolution

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The correction method of computation of heat flux over dome based on turbulence models

The correction method of computation of heat flux over dome ...

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International Symposium on Optoelectronic Technology and Application 2016(OTA 2016)——Conf.12 Infrared Technology and Application

作者： ZHANG Daijun LUO Haibo ZHANG Junchao ZHANG Xiangyue Shenyang Institute of Automation Chinese Academy of Science University of Chinese Academy of Science Key Laboratory of Optical-Electronics Information Processing Chinese Academy of Science Key Laboratory of Image Understanding and Computer Vision

Aerodynamic heating effect caused by high speed flight of optical guidance system will lead to optical dome fracture failure or thermal barrier effect, which results in the inefficiency of the optical

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Theanalysis and test ofthethermal shock resistance of the Multi-spectralCVD ZnS dome

Theanalysis and test ofthethermal shock resistance of the Mu...

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International Symposium on Optoelectronic Technology and Application 2016(OTA 2016)——Conf.12 Infrared Technology and Application

作者： ZHANG Daijun LUO Haibo ZHOU Peipei HOU Xinglin Shenyang Institute of Automation Chinese Academy of Science University of Chinese Academy of Science Key Laboratory of Optical-Electronics Information Processing Chinese Academy of Science Key Laboratory of Image Understanding and Computer Vision

Optical guidance system start infrared guided mode by throwing away the fairing in the terminal guidance phase. After throwing away the fairing, the infrared dome will be suddenly exposed to the aerod

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