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Human 3D pose estimation from a single image is a challenging task with numerous applications. Convolutional Neural Networks (CNNs) have recently achieved superior performance on the task of 2D pose estimation from a single image, by training on images with 2D annotations collected by crowd sourcing. This suggests that similar success could be achieved for direct estimation of 3D poses. However, 3D...
Traditional medical reconstruction system mainly aims at processing medical CT images with clear boundaries. As for those sequence slice images with subtle and unclear boundaries, manual segmentation algorithm are usually adopted. However, they reduce the efficiency greatly. In this paper, we have conducted a series of deep study on these issues, and propose an image segmentation method which combines...
With the rapid growth of computational capability and popularity of mobile phones, Mobile Augmented Reality (MAR) in large scale 3D scenes becomes an emerging field in recent years. The core of MAR is to continuously compute a precise 6 Degree-of-Freedom (DOF) camera pose for each frame, i.e. localization. However, as a crucial part of localization, the 2D-3D points matching is usually inefficient...
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