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Titlebook: Computer Vision -- ECCV 2012. Workshops and Demonstrations; Florence, Italy, Oct Andrea Fusiello,Vittorio Murino,Rita Cucchiara Conference

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樓主: Espionage
41#
發(fā)表于 2025-3-28 16:16:07 | 只看該作者
42#
發(fā)表于 2025-3-28 22:03:15 | 只看該作者
43#
發(fā)表于 2025-3-29 00:29:55 | 只看該作者
Gastric Carcinoma in the Elderlypling MPP using the Reversible Jump Markov Chain Monte Carlo (RJMCMC) algorithm. We also present an evaluation setup to measure the performance of the proposed model. We present results on a variety of images obtained from the Internet to illustrate the performance of the proposed model.
44#
發(fā)表于 2025-3-29 03:15:44 | 只看該作者
45#
發(fā)表于 2025-3-29 08:40:28 | 只看該作者
A Modular Framework for 2D/3D and Multi-modal Segmentation with Joint Super-Resolutionange of machine vision problems. The framework performs a joint segmentation and super-resolution to account for images of unequal resolutions gained from different imaging sensors. This allows to combine high resolution details of one modality with the distinctiveness of another modality. A set of
46#
發(fā)表于 2025-3-29 11:34:43 | 只看該作者
47#
發(fā)表于 2025-3-29 18:07:57 | 只看該作者
Combining Textural and Geometrical Descriptors for Scene Recognitiontion of 3D data also becomes practical. The number of studies that make use of this extra information is increasing. However, their applicabilities are limited due to the need for generic combination methods. In this paper, we propose combining textural and geometrical descriptors for scene recognit
48#
發(fā)表于 2025-3-29 20:25:00 | 只看該作者
49#
發(fā)表于 2025-3-30 00:32:33 | 只看該作者
Human Daily Action Analysis with Multi-view and Color-Depth Datan into consideration and construct a novel dataset of human daily actions. The proposed ACT4. dataset provides synchronized data from 4 views and 2 sources, aiming to facilitate the research of action analysis across multiple views and multiple sources. We also propose a new descriptor of depth info
50#
發(fā)表于 2025-3-30 06:47:31 | 只看該作者
Viewpoint Invariant Matching via Developable Surfaces(RGBD), yet the number of approaches that can take advantage of color and geometry data at the same time is quite limited. We address the topic of wide baseline matching between two RGBD images, i.e. finding correspondences from largely different viewpoints for recognition, model fusion or loop dete
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