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Titlebook: Computer Vision – ECCV 2022; 17th European Confer Shai Avidan,Gabriel Brostow,Tal Hassner Conference proceedings 2022 The Editor(s) (if app

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發(fā)表于 2025-3-21 17:12:30 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Computer Vision – ECCV 2022
副標題17th European Confer
編輯Shai Avidan,Gabriel Brostow,Tal Hassner
視頻videohttp://file.papertrans.cn/235/234261/234261.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Computer Vision – ECCV 2022; 17th European Confer Shai Avidan,Gabriel Brostow,Tal Hassner Conference proceedings 2022 The Editor(s) (if app
描述.The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022..?The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation..
出版日期Conference proceedings 2022
關鍵詞Computer Science; Informatics; Conference Proceedings; Research; Applications
版次1
doihttps://doi.org/10.1007/978-3-031-20077-9
isbn_softcover978-3-031-20076-2
isbn_ebook978-3-031-20077-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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The Economics of Self-Destructive Choiceswe only have labeled images taken under very different conditions (.., indoors). In the real world, it is important that the model trained for both tasks works under various imaging conditions. However, their variation covered by existing labeled hand datasets is limited. Thus, it is necessary to ad
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https://doi.org/10.1007/978-3-031-69118-8rformance drops on small-size datasets, like Cityscapes. In other words, the detection transformers are generally data-hungry. To tackle this problem, we empirically analyze the factors that affect data efficiency, through a step-by-step transition from a data-efficient RCNN variant to the represent
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The Economics of Small Businessesoth day and night, we study multimodal object detection with RGB and thermal cameras, since the latter provides much stronger object signatures under poor illumination. We explore strategies for fusing information from different modalities. Our key contribution is a probabilistic ensembling techniqu
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Small Business in German Manufacturingobustly handle scene changes, our approach deviates from conventional feature point matching, and focuses on the spatial context provided from panorama images. Specifically, we propose efficient color histogram generation and subsequent robust localization using score maps. By utilizing the unique e
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