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Titlebook: Energy Minimization Methods in Computer Vision and Pattern Recognition; 6th International Co Alan L. Yuille,Song-Chun Zhu,Yongtian Wang Con

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發(fā)表于 2025-3-23 11:24:15 | 只看該作者
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發(fā)表于 2025-3-23 13:59:49 | 只看該作者
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發(fā)表于 2025-3-23 21:05:25 | 只看該作者
An Automatic Portrait System Based on And-Or Graph Representationlife-like portraits in different styles from a frontal face image. The system includes three subsystems, each of which models hair, face and collar respectively. The face subsystem can be further decomposed into face components: eyebrows, eyes, nose, mouth, and face contour. Each component has a num
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發(fā)表于 2025-3-24 01:53:49 | 只看該作者
Object Category Recognition Using Generative Template Boostings framework, we integrate the learnable And-Or graph model, a hierarchical structure that combines the reconfigurability of a stochastic context free grammar(SCFG) with the constraints of a Markov random field(MRF), and we sample object configurations as training templates from this generative model
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發(fā)表于 2025-3-24 05:35:26 | 只看該作者
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發(fā)表于 2025-3-24 07:53:13 | 只看該作者
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發(fā)表于 2025-3-24 15:40:55 | 只看該作者
An Effective Multi-level Algorithm Based on Simulated Annealing for Bisecting Graphcept of the graph core. Our experimental evaluations on 18 different graphs show that our algorithm produces encouraging solutions compared with those produced by MeTiS that is a state-of-the-art partitioner in the literature.
19#
發(fā)表于 2025-3-24 22:51:03 | 只看該作者
An Energy Minimisation Approach to Attributed Graph Regularisationnd pattern recognition. To illustrate the general nature of our graph regularisation algorithm, we show results on two application vehicles, photometric stereo and image segmentation. Our experimental results demonstrate the efficacy of our method for both applications under study.
20#
發(fā)表于 2025-3-25 02:56:56 | 只看該作者
CIDER: Corrected Inverse-Denoising Filter for Image Restoration such that the resulting one is an unbiased estimator. Similarly, the wavelet denoising scheme can be applied to suppress the residual noise. Experimental results show that the performance of CIDER is better than other existing methods in our comparison study.
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