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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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发表于 2025-3-21 17:15:34 | 显示全部楼层 |阅读模式
书目名称Computer Vision – ECCV 2022
副标题17th European Confer
编辑Shai Avidan,Gabriel Brostow,Tal Hassner
视频video
丛书名称Lecture Notes in Computer Science
图书封面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
关键词Computer Science; Informatics; Conference Proceedings; Research; Applications
版次1
doihttps://doi.org/10.1007/978-3-031-19827-4
isbn_softcover978-3-031-19826-7
isbn_ebook978-3-031-19827-4Series 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
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发表于 2025-3-21 22:00:05 | 显示全部楼层
,Structure and Motion from Casual Videos,he camera is often roughly stationary (not much parallax), and a large portion of the video may contain moving objects. Under such conditions, state-of-the-art SfM methods tend to produce erroneous results, often failing entirely. To address these issues, we propose CasualSAM, a method to estimate c
发表于 2025-3-22 03:00:55 | 显示全部楼层
,What Matters for 3D Scene Flow Network, scene flow estimation, and it encodes the point motion between two consecutive frames. Thus, it is critical for the flow embeddings to capture the correct overall direction of the motion. However, previous works only search locally to determine a soft correspondence, ignoring the distant points tha
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,GraphCSPN: Geometry-Aware Depth Completion via Dynamic GCNs,as a wide range of applications from robotics to autonomous driving. However, the 3D nature of sparse-to-dense depth completion has not been fully explored by previous methods. In this work, we propose a . .onvolution based .patial .ropagation .etwork (.) as a general approach for depth completion.
发表于 2025-3-22 17:47:09 | 显示全部楼层
,Objects Can Move: 3D Change Detection by Geometric Transformation Consistency,ose a 3D object discovery method that is based only on scene changes. Our method does not need to encode any assumptions about what is an object, but rather discovers objects by exploiting their coherent move. Changes are initially detected as differences in the depth maps and segmented as objects i
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,Beyond Periodicity: Towards a Unifying Framework for Activations in Coordinate-MLPs, grid-based approximations. However, coordinate-MLPs with ReLU activations, in their rudimentary form, demonstrate poor performance in representing signals with high fidelity, promoting the need for positional embedding layers. Recently, Sitzmann . [.] proposed a sinusoidal activation function that
发表于 2025-3-23 06:34:39 | 显示全部楼层
,Deforming Radiance Fields with Cages,is used for scene manipulation or animation. In this paper, we propose a method that enables a new type of deformation of the radiance field: free-form radiance field deformation. We use a triangular mesh that encloses the foreground object called . as an interface, and by manipulating the cage vert
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