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Image Geo-Localization With Cross-Attention, Connor Greenwell
Image Geo-Localization With Cross-Attention, Connor Greenwell
Theses and Dissertations--Computer Science
The problem of estimating the location from which un-geotagged photographs were captured has been well studied by the computer vision community in recent years. The central proposal of this thesis is to define a common framework within which existing approaches can be constructed and evaluated, and to introduce a new method under this framework which uses cross-attention between the query image and a database of satellite imagery with known geotags. Our experiments fit within three broad categories: 1) evaluating the ability of image localization approaches to generalize to unseen regions; 2) examining performance changes under various reference database resolutions, scales, …
Depth Enhancement And Surface Reconstruction With Rgb/D Sequence, Xinxin Zuo
Depth Enhancement And Surface Reconstruction With Rgb/D Sequence, Xinxin Zuo
Theses and Dissertations--Computer Science
Surface reconstruction and 3D modeling is a challenging task, which has been explored for decades by the computer vision, computer graphics, and machine learning communities. It is fundamental to many applications such as robot navigation, animation and scene understanding, industrial control and medical diagnosis. In this dissertation, I take advantage of the consumer depth sensors for surface reconstruction. Considering its limited performance on capturing detailed surface geometry, a depth enhancement approach is proposed in the first place to recovery small and rich geometric details with captured depth and color sequence. In addition to enhancing its spatial resolution, I present a …