Deep learning methods have been more and more widely applied in the field of target
detection. As an important part of deep learning target detection, non-maximum suppression …

Non-maximum suppression is an integral part of the object detection pipeline. First, it sorts
all detection boxes on the basis of their scores. The detection box M with the maximum score …

Pedestrian detection in a crowd is a very challenging issue. This paper addresses this
problem by a novel Non-Maximum Suppression (NMS) algorithm to better refine the …

Machine learning methods have achieved good performance and been widely applied in
various real-world applications. They can learn the model adaptively and be better fit for …

Modern 3D object detectors have immensely benefited from the end-to-end learning idea.
However, most of them use a post-processing algorithm called Non-Maximal Suppression …

Pedestrian detection is an initial step to perform outdoor scene analysis, which plays an
essential role in many real-world applications. Although having enjoyed the merits of deep …

This paper addresses the task of set prediction using deep learning. This is important
because the output of many computer vision tasks, including image tagging and object …

In bin-picking scenarios, multiple instances of an object of interest are stacked in a pile
randomly, and hence, the instances are inherently subjected to the challenges: severe …