Abstract: As self-driving technology continues to become more popular and used, the object detection task in the perception system of self-driving vehicles has gained more and more attention, in which ...
Abstract: Point cloud sampling aims to derive a sparse point cloud from a relatively dense point cloud, which is essential for efficient data transmission and storage. While existing deep sampling ...
Although inherently challenging, the quantification of vehicle emissions has evolved considerably in recent decades and now extends well beyond the original lab-based measurements. Here we’ll explain ...
ModelNet40: https://shapenet.cs.stanford.edu/media/modelnet40_normal_resampled.zip ScanObjectNN: https://docs.google.com/forms/d/e ...
Test-Time Adaptation (TTA) addresses distribution shifts during testing by adapting a pretrained model without access to source data. In this work, we propose a novel TTA approach for 3D point cloud ...
Discrepancy theory investigates the uniformity of distributions by quantifying the deviation between the empirical distribution of a finite set of points and the uniform distribution. In numerical ...
Describe the abstract idea of a sampling distribution and how it reflects the sample to sample variability of a sample statistic or point estimate. Identify the ...
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