Name
Title | ||
|---|---|---|
Point-cloud based 3D object detection and classification methods for self-driving applications: A survey and taxonomy |
Abstract | ||
|---|---|---|
•A comprehensive review of 3D Object Detection for driverless vehicles is provided.•A generic pipeline architecture is proposed to describe the models workflow.•Taxonomies are proposed to categorize the existing models regarding design choices.•A comparative study for models is conducted and the relevant resources released.•The current challenges and future trends of multi-focus image fusion are discussed. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.inffus.2020.11.002 | Information Fusion |
Keywords | DocType | Volume |
Autonomous vehicles,Computer vision,Deep learning,Perception,LiDAR,3D object detection models | Journal | 68 |
ISSN | Citations | PageRank |
1566-2535 | 6 | 0.59 |
References | Authors | |
0 | 9 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Duarte Fernandes | 1 | 6 | 0.59 |
| António Silva | 2 | 7 | 3.69 |
| Rafael Névoa | 3 | 6 | 0.59 |
| Cláudia Simões | 4 | 6 | 0.59 |
| Dibet Gonzalez | 5 | 6 | 0.59 |
| Miguel Guevara | 6 | 6 | 0.59 |
| Paulo Novais | 7 | 883 | 171.45 |
| João P. Monteiro | 8 | 50 | 7.04 |
| Pedro Melo-Pinto | 9 | 6 | 0.59 |