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pro vyhledávání: '"Di, Huijun"'
Humans naturally rely on floor plans to navigate in unfamiliar environments, as they are readily available, reliable, and provide rich geometrical guidance. However, existing visual navigation settings overlook this valuable prior knowledge, leading
Externí odkaz:
http://arxiv.org/abs/2412.18335
Recently, numerous algorithms have been developed to tackle the problem of light field super-resolution (LFSR), i.e., super-resolving low-resolution light fields to gain high-resolution views. Despite delivering encouraging results, these approaches
Externí odkaz:
http://arxiv.org/abs/2201.00346
In this paper, we present a decomposition model for stereo matching to solve the problem of excessive growth in computational cost (time and memory cost) as the resolution increases. In order to reduce the huge cost of stereo matching at the original
Externí odkaz:
http://arxiv.org/abs/2104.07516
Cost aggregation is a key component of stereo matching for high-quality depth estimation. Most methods use multi-scale processing to downsample cost volume for proper context information, but will cause loss of details when upsampling. In this paper,
Externí odkaz:
http://arxiv.org/abs/2006.03209
Akademický článek
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Publikováno v:
In Neurocomputing 3 September 2020 404:227-239
Stochastic sampling based trackers have shown good performance for abrupt motion tracking so that they have gained popularity in recent years. However, conventional methods tend to use a two-stage sampling paradigm, in which the search space needs to
Externí odkaz:
http://arxiv.org/abs/1410.7484
Publikováno v:
In Signal Processing: Image Communication May 2019 74:162-174
Publikováno v:
In Neurocomputing 17 December 2018 322:195-205
Publikováno v:
In Neurocomputing 19 July 2017 247:1-15