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Titlebook: Large-Scale Visual Geo-Localization; Amir R. Zamir,Asaad Hakeem,Richard Szeliski Book 2016 Springer International Publishing Switzerland 2

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51#
發(fā)表于 2025-3-30 11:57:50 | 只看該作者
52#
發(fā)表于 2025-3-30 13:57:03 | 只看該作者
Adaptive Rendering for Large-Scale Skyline Characterization and Matchings and images. Given an image, our system automatically extracts the skyline and then matches it to a database of reference skylines generated from rendered images using digital elevation data (DEM). The sampling density of these rendering locations determines both the accuracy and the speed of skyli
53#
發(fā)表于 2025-3-30 17:15:00 | 只看該作者
54#
發(fā)表于 2025-3-30 21:47:00 | 只看該作者
55#
發(fā)表于 2025-3-31 04:17:47 | 只看該作者
56#
發(fā)表于 2025-3-31 05:26:25 | 只看該作者
57#
發(fā)表于 2025-3-31 11:43:13 | 只看該作者
Worldwide Pose Estimation Using 3D Point Clouds and bidirectional matching of image features with 3D points. We evaluate our method on several large datasets, and show state-of-the-art results on landmark recognition as well as the ability to locate cameras to within meters, requiring only seconds per query.
58#
發(fā)表于 2025-3-31 13:53:36 | 只看該作者
Adaptive Rendering for Large-Scale Skyline Characterization and Matchingne matching. The proposed approach successfully combines global planning and local greedy search strategies to select new rendering locations incrementally. We report quantitative and qualitative results from synthesized and real experiments, where we achieve a computational speedup of around 4X.
59#
發(fā)表于 2025-3-31 20:43:40 | 只看該作者
60#
發(fā)表于 2025-4-1 00:40:37 | 只看該作者
Semantically Guided Geo-location and Modeling in Urban Environmentsene layouts in the reference dataset. We will demonstrate the effectiveness of these semantic representations on examples of localization, semantic concept discovery, and intersection recognition in the images of urban scenes.
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