Geometry and Uncertainty-Aware 3D Point Cloud Class-Incremental Semantic Segmentation

Despite the significant recent progress made on 3D point cloud semantic segmentation, the current methods require training data for all classes at once, and are not suitable for real-life scenarios where new categories are being continuously discovered. Substantial memory storage and expensive re-tr...

Celý popis

Podrobná bibliografia

Vydané v:	Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) s. 21759 - 21768
Hlavní autori:	Yang, Yuwei, Hayat, Munawar, Jin, Zhao, Ren, Chao, Lei, Yinjie
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.06.2023
Predmet:	continual low-shot meta or long-tail learning Point cloud compression Semantic segmentation Semantics Solid modeling Three-dimensional displays Training Transfer Upper bound
ISSN:	1063-6919
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!