The last couple of months, I have been looking into the newest extension of the popular PointNet and PointNet++ architectures called PointNeXt - a deep learning architecture for solving 3D point clouds tasks e.g. classification and semantic segmentation.
PointNeXt got released back in the beginning of June this year (2022) and the PointNeXt paper very recently got accepted...
The mean Intersection over Union (mIoU) is a metric which is often used for measuring the goodness of e.g. 2D- and 3D semantic segmentation and object detection systems, by comparing the predictions made by a system to the ground truth labels. In this post, we will show how the mIoU is calculated for a very simple 3D point cloud toy example...
Object detection is a very well-studied subject, which is used in many useful and exciting applications today, such as for tracking objects (speed, position etc.), in surveillance system, for anomaly detection, for sorting and filtering objects on assembly lines, for counting (e.g. how many people are visiting the central station every day and how many cars are passing by this...
Recently, I have grown a big interest in various learning methods, for deep learning models, which tries to utilize unlabeled data such as semi-supervised learning and self-supervised learning. I am definitely not the only one. The topics are more generally called representation learning and it is receiving a great deal of attention in the deep learning research community these days.
The reason...