3DzAL performs zero-shot 3D anomaly localization by combining contrastive patch learning, a normalcy classifier, and adversarial perturbation on pseudo-anomalies generated from task-irrelevant point clouds.
Col- laborative discrepancy optimization for reliable image anomaly localization
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.CV 1years
2024 1verdicts
CONDITIONAL 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
Towards Zero-shot 3D Anomaly Localization
3DzAL performs zero-shot 3D anomaly localization by combining contrastive patch learning, a normalcy classifier, and adversarial perturbation on pseudo-anomalies generated from task-irrelevant point clouds.