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Titlebook: Advances in Visual Computing; 10th International S George Bebis,Richard Boyle,Mark Carlson Conference proceedings 2014 Springer Internation

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楼主: Consonant
发表于 2025-3-23 11:06:34 | 显示全部楼层
Direct Estimation of Dense Scene Flow and Depth from a Monocular Sequence large scale sparse system of linear equations, which we order so that the corresponding matrix is symmetric positive definite. This implies that Gauss-Seidel iterations converge, point-wise or block-wise, and afford highly efficient means of solving the equations. Examples are given to verify the scheme and its implementation.
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Efficient Object Localization and Segmentation in Weakly Labeled Videosrk. Our method does not require user inputs or object detectors, so it can be potentially applied to videos of any object categories. We evaluate our method on a dataset consisting of more than 100 video shots of 10 different object categories. Our experimental results show that our method outperforms other baseline approaches.
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发表于 2025-3-24 01:33:18 | 显示全部楼层
Visual Tracking Extensions for Accurate Target Recovery in Low Frame Rate Videos large data set of videos for tracking, we show that our method not only outperforms other related benchmarks in the field, but it also achieves better results both visually and quantitatively, once compared to actual ground truth data.
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https://doi.org/10.1007/978-1-4615-6051-7 show that our proposed algorithm not only enhances the contrast but also preserves the details and sharp edges. Our results demonstrate the effectiveness of the proposed optimization algorithm for dehazing.
发表于 2025-3-24 18:08:22 | 显示全部楼层
Peggy L. Fiedler,Peter M. KareivapenGL z-testing performance. Two execution models have been implemented (per-line parallel, and per-pixel parallel) and tested against standard video-plus-depth test sequences to show the approach performance.
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The Conservation of Habitat and Landscape, account for occluded regions. Rather than warping frames or precomputing a large grid of derivatives, MB-CLG warps the flows at each iteration. This leads to lower computational cost, and requires less data storage. Based on the results for various sequences, MB-CLG outperforms existing optical flow methods in the sense of AAE, AEP and MSE.
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