Towards a Weakly Supervised Framework for 3D Point Cloud Object Detection and Annotation
It is quite laborious and costly to manually label LiDAR point cloud data for training high-quality 3D object detectors. This work proposes a weakly supervised framework which allows learning 3D detection from a few weakly annotated examples. This is achieved by a two-stage architecture design. Stag...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 44(2022), 8 vom: 01. Aug., Seite 4454-4468
|
|---|
| 1. Verfasser: |
Meng, Qinghao
(VerfasserIn) |
|---|
| Weitere Verfasser: |
Wang, Wenguan,
Zhou, Tianfei,
Shen, Jianbing,
Jia, Yunde,
Van Gool, Luc |
|---|
| Format: | Online-Aufsatz
|
|---|
| Sprache: | English |
|---|
| Veröffentlicht: |
2022
|
|---|
| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
|
|---|
| Schlagworte: | Journal Article
Research Support, Non-U.S. Gov't |
|---|