ELATE 发表于 2025-3-25 06:18:36

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Proclaim 发表于 2025-3-25 08:30:48

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dialect 发表于 2025-3-25 15:41:34

Geometric and Semantic Modeling from RGB-D Datal overview recent efforts on this research topic, in particular, research using advanced machine learning techniques, exploiting the complementary characteristics of geometry and image information in RGB-D data, and incorporating prior knowledge.

卡死偷电 发表于 2025-3-25 16:34:19

Real-Time Hand Pose Estimation Using Depth Camerac regression method that directly regresses holistic 3D hand pose; (2) point-set-based point-wise regression method that generates dense outputs for robust 3D hand pose estimation. Extensive experiments are conducted to evaluate the effectiveness of these two methods. We will also discuss the limitations and advantages of the proposed methods.

漂泊 发表于 2025-3-25 22:36:45

RGB-D Salient Object Detection: A Review since many RGB-D salient object detection methods derive from the existing RGB ones. Next, we present the typical RGB-D salient object detection methods, evaluate their performance on public datasets, and summarize their issues. Finally, we discuss some open problems and suggestions for future research.

让步 发表于 2025-3-26 03:22:57

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大笑 发表于 2025-3-26 07:11:05

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全能 发表于 2025-3-26 11:32:15

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Insubordinate 发表于 2025-3-26 15:50:10

Oscar Meruvia-Pastorcal specimen preparation to three-dimensional images of the .Electron tomography has become a standard technique with applications in cell biology, structural biology, and materials science. This definitive work provides a comprehensive treatment of the mathematical background and working methods of

Hay-Fever 发表于 2025-3-26 20:23:39

imaging method provides full 3D structural information at much higher resolution (typically 5–10 nm) than is attainable by light microscopy, and can be applied to cells and organelles that are maintained in a state that is as close to native as can be achieved currently in electron microscopy. Not o
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查看完整版本: Titlebook: RGB-D Image Analysis and Processing; Paul L. Rosin,Yu-Kun Lai,Yonghuai Liu Book 2019 Springer Nature Switzerland AG 2019 RGB-D Images.Comp