Defect-aware Hybrid Prompt Optimization via Progressive Tuning for Zero-Shot Multi-type Anomaly Detection and Segmentation

arXiv:2512.09446 · cs.CV · Submitted 2025-12-10 · Read on arXiv

cs.CV

Submitted: 2025-12-10

Updated: 2026-07-02

Code: https://github.com/boschresearch/defect-aware-prompt-optimization

Terminology

• Distribution Shift — 29× in this paper · explained in 5 episodes
• Embeddings — 23× in this paper · explained in 2 episodes
• AUC — 13× in this paper · explained in 2 episodes
• Benchmark — 13× in this paper · explained in 2 episodes
• Ablation — 11× in this paper · explained in 1 episode
• Alignment — 6× in this paper · explained in 1 episode
• Robustness — 6× in this paper · explained in 5 episodes
• Fine-Tuning — 4× in this paper · explained in 5 episodes
• Generalization — 4× in this paper · explained in 13 episodes
• Accuracy — 3× in this paper · explained in 1 episode
• Adam — 3× in this paper · explained in 2 episodes
• Aggregation — 3× in this paper · explained in 1 episode
• Loss Function — 3× in this paper · explained in 2 episodes
• Modality Gap — 3× in this paper · explained in 4 episodes
• Vision-Language Models (VLMs) — 3× in this paper · explained in 6 episodes
• Ablation study — 2× in this paper · explained in 1 episode
• Adaptation — 2× in this paper · explained in 1 episode
• Cosine Similarity — 2× in this paper · explained in 3 episodes
• Distillation — 2× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• CLIP with the Segment Anything Model — 1× in this paper
• Domain Shift — 1× in this paper · explained in 4 episodes
• F1 Score — 1× in this paper · explained in 3 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Knowledge Distillation — 1× in this paper · explained in 11 episodes
• Knowledge Graph — 1× in this paper · explained in 7 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Segment Anything Model (SAM) — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• True Positive Rate — 1× in this paper
• Variational Bayes — 1× in this paper · explained in 2 episodes

Sources

• APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD
• Sub-Image Anomaly Detection with Deep Pyramid Correspondences
• Adam: A Method for Stochastic Optimization
• Dice Loss for Data-imbalanced NLP Tasks
• Unsupervised Two-Stage Anomaly Detection
• MultiADS: Defect-aware Supervision for Multi-type Anomaly Detection and Segmentation in Zero-Shot Learning
• DFR: Deep Feature Reconstruction for Unsupervised Anomaly Segmentation
• Bridging Language and Action: A Survey of Language-Conditioned Robot Manipulation

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