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Titlebook: Energy Minimization Methods in Computer Vision and Pattern Recognition; 7th International Co Daniel Cremers,Yuri Boykov,Frank R. Schmidt Co

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樓主: emanate
41#
發(fā)表于 2025-3-28 17:46:51 | 只看該作者
42#
發(fā)表于 2025-3-28 21:39:58 | 只看該作者
Bipartite Graph Matching Computation on GPUnnecting them. Each edge selected has no common node as its end points to any other edge within the subset. When the considered graph has huge sets of nodes and edges the sequential approaches are impractical, specially for applications demanding fast results. In this paper we investigate how to com
43#
發(fā)表于 2025-3-28 23:01:58 | 只看該作者
44#
發(fā)表于 2025-3-29 07:03:00 | 只看該作者
Parallel Hidden Hierarchical Fields for Multi-scale Reconstructionle phenomena frequently possess nonstationary, piece-wise multi-model behaviour, the classic hidden Markov method can not perform well in modeling such complex images. In this paper we provide a new modeling approach to extend previous hierarchical methods, with multiple hidden fields, to perform re
45#
發(fā)表于 2025-3-29 10:23:50 | 只看該作者
46#
發(fā)表于 2025-3-29 13:59:15 | 只看該作者
47#
發(fā)表于 2025-3-29 18:19:03 | 只看該作者
A PDE Approach to Coupled Super-Resolution with Non-parametric Motionrate motion estimation among the low-resolution measurements is a fundamental challenge of the super-resolution problem. Some recent promising advances in this area have been focused on coupling or combing the super-resolution reconstruction and the motion estimation. However, the existing approach
48#
發(fā)表于 2025-3-29 20:32:20 | 只看該作者
On a Decomposition Model for Optical Flow is realized by reformulating the optical flow problem first as a variational denoising problem for multi-channel data and then by applying decomposition methods. Thanks to the general formulation, several norms can be used for the decomposition. We study a decomposition for the optical flow into bo
49#
發(fā)表于 2025-3-30 01:13:12 | 只看該作者
A Schr?dinger Wave Equation Approach to the Eikonal Equation: Application to Image Analysis the solution to the corresponding Schr?dinger equation. When the forcing function .(.) is set to one, we get the Euclidean distance function problem. We show that the corresponding Schr?dinger equation has a closed form solution which can be expressed as a discrete convolution and efficiently compu
50#
發(fā)表于 2025-3-30 07:13:32 | 只看該作者
A Local Normal-Based Region Term for Active Contours background, preventing their use in natural images. We introduce a more flexible local region energy achieving a trade-off between local features of gradient-like terms and global region features. Relying on the theory of parallel curves, we define our region term using constant length lines normal
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