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Titlebook: Computer Vision -- ECCV 2014; 13th European Confer David Fleet,Tomas Pajdla,Tinne Tuytelaars Conference proceedings 2014 Springer Internati

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樓主: fibrous-plaque
21#
發(fā)表于 2025-3-25 04:48:23 | 只看該作者
https://doi.org/10.1057/9781137328113o develop a simple but effective approach to obtain the clustering result of faces. Moreover, after using several acceleration techniques, our proposed method is suitable for solving large-scale problems. The experimental results on two benchmark datasets demonstrate the effectiveness of our approach.
22#
發(fā)表于 2025-3-25 10:52:59 | 只看該作者
M. Rapp M.D.,K. -K. Dittel M.D.educed to solving a succession of simple integer programs, leading to increased efficiency in both memory and speed. To validate our method, we present experimental results on the PASCAL VOC 2007 dataset for images and the YouTube-Objects dataset for videos, as well as a joint combination of the two.
23#
發(fā)表于 2025-3-25 14:05:38 | 只看該作者
Solving Square Jigsaw Puzzles with Loop Constraintsruction accuracy. For the most challenging type of image puzzles with unknown piece rotation we reduce the reconstruction error by up to 70%. We determine an upper bound on reconstruction accuracy for various data sets and show that, in some cases, our algorithm nearly matches the upper bound.
24#
發(fā)表于 2025-3-25 16:51:05 | 只看該作者
Weighted Block-Sparse Low Rank Representation for Face Clustering in Videoso develop a simple but effective approach to obtain the clustering result of faces. Moreover, after using several acceleration techniques, our proposed method is suitable for solving large-scale problems. The experimental results on two benchmark datasets demonstrate the effectiveness of our approach.
25#
發(fā)表于 2025-3-25 23:53:48 | 只看該作者
Efficient Image and Video Co-localization with Frank-Wolfe Algorithmeduced to solving a succession of simple integer programs, leading to increased efficiency in both memory and speed. To validate our method, we present experimental results on the PASCAL VOC 2007 dataset for images and the YouTube-Objects dataset for videos, as well as a joint combination of the two.
26#
發(fā)表于 2025-3-26 03:01:10 | 只看該作者
27#
發(fā)表于 2025-3-26 04:53:57 | 只看該作者
28#
發(fā)表于 2025-3-26 10:34:24 | 只看該作者
29#
發(fā)表于 2025-3-26 13:16:21 | 只看該作者
30#
發(fā)表于 2025-3-26 19:51:15 | 只看該作者
https://doi.org/10.1007/978-3-7985-1842-1video, we formulate the optimization problem as minimizing the pixel error between the blurred frames and images synthesized from the model, and solve it using gradient descent. We demonstrate our approach on synthetic and real sequences.
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