Deep Learning for 3D Point Clouds - A Survey

Introduction

Point cloud is point sets defined in 3D metric space. Point cloud has become one of the most significant data format for 3D representation. Its gaining increased popularity as a result of increased availability of acquisition devices, such as LiDAR, as well as increased application in areas such as robotics, autonomous driving, augmented and virtual reality I have studied the Survey paper in detail and published a short story of my understanding.

Learnings

1. The Survey presented a contemporary survey of the state-of-the-art methods for 3D understanding, including 3D shape classification, 3D object detection & tracking, and 3D scene and object segmentation.
2. A comprehensive taxonomy and performance comparison of these methods was presented.
3. Merits and demerits of various methods were also covered, with potential research directions being listed.

Deliverables

Medium Article Link:

https://medium.com/@vijaylaxmi.nagurkar/deep-learning-for-3d-point-clouds-b40a04a45726

Slideshare Link:

https://www.slideshare.net/VijaylaxmiNagurkar/deep-learning-for-3-d-point-clouds-presentation

Short Movie Recording

https://youtu.be/CpW6wRwxOjM

References

https://arxiv.org/abs/1912.12033