Occlusion Problem in 3D Object Detection: A Review

In computer vision, 3D object detection has numerous applications such as robotics, augmented reality (AR), medical field, manufacturing industries, and safe autonomous driving. But the real-object detection may involve various problems such as noise, missing data, and occlusion problem. From past few years, the great progress in 3D object detection has been made. Object recognition and identification in occlusion remain a difficult challenge, despite recent breakthroughs in 3D object detection. The occlusion problem is one of the difficulties in object tracking. The paper highlights a number of research hurdles and open concerns that researchers must address.