A direct feature-space approach for 3D LiDAR anomaly segmentation achieves competitive results on existing and new mixed real-synthetic datasets.
Generalization of the lam- bertian model and implications for machine vision.IJCV, 14 (3):227–251, 1995
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Learning to Identify Out-of-Distribution Objects for 3D LiDAR Anomaly Segmentation
A direct feature-space approach for 3D LiDAR anomaly segmentation achieves competitive results on existing and new mixed real-synthetic datasets.