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Titlebook: Computer Vision -- ACCV 2014; 12th Asian Conferenc Daniel Cremers,Ian Reid,Ming-Hsuan Yang Conference proceedings 2015 Springer Internation

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樓主: DUCT
31#
發(fā)表于 2025-3-26 21:53:32 | 只看該作者
The Czech and Slovak Experiencespatial distances. We adopt a strategy of local competition and global Angular Embedding to integrate pairwise orders into a globally consistent order, taking their reliability into account. Experiments on the MIT Intrinsic Image dataset and the UIUC Shadow dataset show that our model can effectivel
32#
發(fā)表于 2025-3-27 01:36:52 | 只看該作者
Springer Tracts in Advanced Robotics energy of the coefficients, and when the estimated target can be well approximated by the normal templates, we dynamically update the template set to reduce the drifting problem. Experimental results show that the proposed BReT algorithm outperforms state-of-the-art trackers on blurred sequences.
33#
發(fā)表于 2025-3-27 08:50:18 | 只看該作者
34#
發(fā)表于 2025-3-27 10:01:19 | 只看該作者
https://doi.org/10.1057/9780230210813hin different time periods. Finally, we propose to update the CNN model in a “l(fā)azy” style to speed-up the training stage, where the network is updated only when a significant appearance change occurs on the object, without sacrificing tracking accuracy. The CNN tracker outperforms all compared state
35#
發(fā)表于 2025-3-27 14:43:14 | 只看該作者
36#
發(fā)表于 2025-3-27 21:37:16 | 只看該作者
Eleonora Loi,Patrizia Zavattari and MSRC-12 gesture dataset and achieves comparable performance to the state-of-the-art on MSR action 3D dataset. Moreover, experimental results show that our method is very intuitive and robust to noise and temporal variation.
37#
發(fā)表于 2025-3-27 22:49:01 | 只看該作者
38#
發(fā)表于 2025-3-28 03:00:25 | 只看該作者
The Crippling Legacy of Monomanias in DSM-5 updating observation model, we adopt on an online robust PCA during the update of observation model. Our qualitative and quantitative evaluations on challenging dataset demonstrate that the proposed scheme is competitive to several sophisticated state of the art methods, and it is much faster.
39#
發(fā)表于 2025-3-28 09:12:06 | 只看該作者
40#
發(fā)表于 2025-3-28 14:12:36 | 只看該作者
https://doi.org/10.1007/978-3-319-16814-2information retrieval; large datasets; machine learning; multi-view stereo; video segmentation
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