evanescent
发表于 2025-3-23 10:11:40
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Credence
发表于 2025-3-23 15:57:16
https://doi.org/10.1007/978-3-658-30567-3Non-Rigid Structure from Motion; NRSfM; Scalable Monocular Surface Reconstruction; Shape Priors for Non
Uncultured
发表于 2025-3-23 18:24:13
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Antagonism
发表于 2025-3-23 23:13:00
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依法逮捕
发表于 2025-3-24 03:42:50
Preliminaries,is at hand. The chapter is organised into three sections, each of which follows an individual common thread. In Sec. 2.1, starting from an overview of the imaging models, we review Hadamard problem classification, basics of the theory of inverse problems and non-linear least squares.
Repatriate
发表于 2025-3-24 09:32:40
Scalable Dense Non-Rigid Structure from Motion, is not only obtaining accurate reconstructions but also the results have to remain consistently accurate with the different number of input point tracks and for as many different scenarios as possible.
BALK
发表于 2025-3-24 12:26:31
Coherent Depth Fields with High Dimensional Space Model,tial regulariser and the new deformation model come, on the one hand, from handling occlusions, and, on the other hand, from a requirement to be able to compress the reconstructions which is espacially relevant in endoscopic applications as well as for saving the reconstructions.
cunning
发表于 2025-3-24 16:10:44
Probabilistic Point Set Registration with Prior Correspondences, prior knowledge which can be embedded into point set registration should not exceed some “critical mass” in the sense that otherwise, the algorithmic class will change. For instance, registration of watertight meshes is known as mesh registration.
袋鼠
发表于 2025-3-24 21:02:14
Review of Previous Work,THE core problems in this thesis, . monocular non-rigid 3D reconstruction and point set registration, are reviewed in this chapter. For every problem, we discuss method classes for solving them and relevant previous works. In some following chapters, we also additionally elaborate on most related methods for the respective proposed approaches.
Annotate
发表于 2025-3-25 01:50:41
Shape Priors in Dense Non-Rigid Structure from Motion,THIS chapter is devoted to two NRSfM methods with shape priors obtained on-the-fly. Both static and dynamic shape priors are investigated. . refers to a single prior 3D state, and . refers to a series of states.