MADPOT adapts CLIP with learnable prompts, partial optimal transport, and contrastive learning, reporting state-of-the-art anomaly detection AUC on the BMAD benchmark in few-shot and zero-shot settings.
SIAM Journal on Scientific Computing37(2), A1111–A1138 (2015)
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
MADPOT: Medical Anomaly Detection with CLIP Adaptation and Partial Optimal Transport
MADPOT adapts CLIP with learnable prompts, partial optimal transport, and contrastive learning, reporting state-of-the-art anomaly detection AUC on the BMAD benchmark in few-shot and zero-shot settings.