英文摘要:The task of estimating camera poses can be enhanced through novel view synthesis techniques such as NeRF and Gaussian Splatting to increase the diversity and extension of training data. However, these techniques often produce rendered images with issues like blurring and ghosting, which compr...
The Great Grading Scale(TGGS) uses a grading curve spreadsheet to execute “how to grade on a curve” when percent test scores need a curve other than a standard bell curve. Often, percent scores from a challenging test demand that some adjustment be made in order to be fair to the stud...
As a result, points within the areas with insufficient initializing points can be grown more effectively, leading to a more accurate and detailed reconstruction. In addition, we propose a simple yet effective strategy to scale the gradient field according to the distance to the camera, to...
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Our approach represents the human as a set of 3D Gaussians within a canonical space, whose articulation is defined by extending the skinning of the underlying SMPL geometry to arbitrary locations in the canonical space. To account for pose-dependent effects, we introduce a SE(3) field, which ...
enough to obtain a sufficiently low duty cycle at 500 Hz, the output current could increase again, in strong overcurrent or short circuit conditions. For this reason the switching frequency is also reduced to keep the inductor current within its maximum threshold limit. The frequency depends...
of human resources within the Company, promote individual growth and engagement, and accelerate the creation of new value. Developing leaders with global perspectives is essential for the Group‘s sustainable growth. Accordingly, we not only encourage human resource mobility among businesses, we also ...
However, as the grade levels increase in the 2015 program, the gains in the affective domain increase. In the 2018 program, it is seen that affective field objectives do not differ between grade levels. When the distribution is examined according to Simpson's Ps...
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To eliminate the need for accurate pose input during reconstruction, we anchor one input view's local camera coordinates as the canonical space and train the network to predict Gaussian primitives for all views within this space. This approach obviates the need to transform Gaussian primitives from...