ORBIT
发表于 2025-3-26 23:55:38
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Irremediable
发表于 2025-3-27 03:07:00
Spatio-Temporally Consistent Correspondence for Dense Dynamic Scene Modelingcal image sequences. The obtained results for these two problems on multiple publicly available dynamic reconstruction datasets illustrate both the effectiveness and generality of our proposed approach.
性学院
发表于 2025-3-27 05:50:23
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entreat
发表于 2025-3-27 12:19:17
Visualizing Image Priors to study various popular image models, and reveal interesting behaviors, which were not noticed in the past. We confirm our findings through denoising experiments. These validate that the structures we reveal as ‘optimal’ for a specific prior are indeed better denoised by this prior.
玩笑
发表于 2025-3-27 16:02:55
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Valves
发表于 2025-3-27 18:16:17
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肥料
发表于 2025-3-27 23:58:13
Deep Learning 3D Shape Surfaces Using Geometry Imagescut to convert the original 3D shape into a flat and regular geometry image. We propose a way to implicitly learn the topology and structure of 3D shapes using geometry images encoded with suitable features. We show the efficacy of our approach to learn 3D shape surfaces for classification and retrieval tasks on non-rigid and rigid shape datasets.
INERT
发表于 2025-3-28 02:30:51
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Crepitus
发表于 2025-3-28 07:27:15
Learning Semantic Deformation Flows with 3D Convolutional Networksdetail information. Our experiments show that the CNN approach achieves comparable results with state of the art methods when applied to CAD models. When applied to single frame depth scans, and partial/noisy CAD models we achieve . less error compared to the state-of-the-art.
终止
发表于 2025-3-28 12:30:38
Conference proceedings 2016eo: events, activities and surveillance; applications. They are organized in topical sections on detection, recognition and retrieval; scene understanding; optimization; image and video processing; learning; action, activity and tracking; 3D; and 9 poster sessions..