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Full-Text Articles in Physical Sciences and Mathematics
Multi-Domain Adaptation For Image Classification, Depth Estimation, And Semantic Segmentation, Yu Zhang
Multi-Domain Adaptation For Image Classification, Depth Estimation, And Semantic Segmentation, Yu Zhang
Theses and Dissertations--Computer Science
The appearance of scenes may change for many reasons, including the viewpoint, the time of day, the weather, and the seasons. Traditionally, deep neural networks are trained and evaluated using images from the same scene and domain to avoid the domain gap. Recent advances in domain adaptation have led to a new type of method that bridges such domain gaps and learns from multiple domains.
This dissertation proposes methods for multi-domain adaptation for various computer vision tasks, including image classification, depth estimation, and semantic segmentation. The first work focuses on semi-supervised domain adaptation. I address this semi-supervised setting and propose …
Revisiting Absolute Pose Regression, Hunter Blanton
Revisiting Absolute Pose Regression, Hunter Blanton
Theses and Dissertations--Computer Science
Images provide direct evidence for the position and orientation of the camera in space, known as camera pose. Traditionally, the problem of estimating the camera pose requires reference data for determining image correspondence and leveraging geometric relationships between features in the image. Recent advances in deep learning have led to a new class of methods that regress the pose directly from a single image.
This thesis proposes methods for absolute camera pose regression. Absolute pose regression estimates the pose of a camera from a single image as the output of a fixed computation pipeline. These methods have many practical benefits …