InCTRLv2 extends InCTRL with discriminative and one-class anomaly score learning modules to achieve state-of-the-art few-shot generalist anomaly detection and segmentation across ten datasets.
Destseg: Segmentation guided denoising student-teacher for anomaly detection, 2023b
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Combines visual prompting, dual-teacher supervision, and diffusion augmentation on an MMR backbone to gain 3.5 percentage points on the AeBAD anomaly detection dataset.
citing papers explorer
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InCTRLv2: Generalist Residual Models for Few-Shot Anomaly Detection and Segmentation
InCTRLv2 extends InCTRL with discriminative and one-class anomaly score learning modules to achieve state-of-the-art few-shot generalist anomaly detection and segmentation across ten datasets.
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Visual Prompting Meets Feature Reconstruction-Based Anomaly Detection with Dual-Teacher Supervision
Combines visual prompting, dual-teacher supervision, and diffusion augmentation on an MMR backbone to gain 3.5 percentage points on the AeBAD anomaly detection dataset.