Bin-Bin Gao

8

Papers

173

Total Citations

Papers (8)

Real-IAD: A Real-World Multi-View Dataset for Benchmarking Versatile Industrial Anomaly Detection

Few-Shot Anomaly-Driven Generation for Anomaly Classification and Segmentation

Learning to Detect Multi-class Anomalies with Just One Normal Image Prompt

MMAD: A Comprehensive Benchmark for Multimodal Large Language Models in Industrial Anomaly Detection

MatchDet: A Collaborative Framework for Image Matching and Object Detection

Real-IAD D³: A Real-World 2D/Pseudo-3D/3D Dataset for Industrial Anomaly Detection

Unsupervised Continual Anomaly Detection with Contrastively-Learned Prompt

Learning Task-Aware Language-Image Representation for Class-Incremental Object Detection