FLASH: A "Generate Once, Synthesize Many" Framework for Synthetic Anomaly Generation in Industrial Anomaly Detection

arXiv:2609.37314 · cs.CV · Submitted 2026-09-29 · Read on arXiv

cs.CV

Submitted: 2026-09-29

Updated: 2026-09-29

Code: https://github.com/AbhayKumarDas/flash

Terminology

• Calibration — 42× in this paper · explained in 7 episodes
• alpha — 13× in this paper · explained in 1 episode
• Benchmark — 7× in this paper · explained in 2 episodes
• Alignment — 6× in this paper · explained in 1 episode
• Object Boundary Suppression — 5× in this paper
• F1 Score — 4× in this paper · explained in 3 episodes
• Degeneracy — 3× in this paper · explained in 3 episodes
• Diffusion Model — 3× in this paper · explained in 8 episodes
• Distillation — 3× in this paper · explained in 2 episodes
• Fidelity — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Core — 2× in this paper · explained in 2 episodes
• Failure Modes — 2× in this paper · explained in 3 episodes
• Hysteresis — 2× in this paper · explained in 3 episodes
• Multi-Resolution Spectral Pyramid — 2× in this paper
• Vision-language models — 2× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Cross-Model Transfer — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Feature Selection — 1× in this paper · explained in 4 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Model-Agnostic — 1× in this paper · explained in 2 episodes
• Over-smoothing — 1× in this paper · explained in 4 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Vision Language Model — 1× in this paper

Sources

• Qwen2.5-VL Technical Report
• The MVTec AD 2 Dataset: Advanced Scenarios for Unsupervised Anomaly Detection
• MIRAGE: Model-agnostic Industrial Realistic Anomaly Generation and Evaluation for Visual Anomaly Detection
• GPT-4o System Card
• DINOv3
• AnoStyler: Text-Driven Localized Anomaly Generation via Lightweight Style Transfer
• A Survey on Industrial Anomaly Synthesis
• ASBench: Image Anomalies Synthesis Benchmark for Anomaly Detection

Related papers

• Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
• AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories
• Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
• MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal MRI Segmentation
• TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
• A Survey on Efficient Vision-Language-Action Models