Bin-Bin Gao

papers

309

total citations

papers (10)

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

CVPR 2024arXiv

127

citations

Unsupervised Continual Anomaly Detection with Contrastively-Learned Prompt

AAAI 2024arXiv

citations

Decoupling Classifier for Boosting Few-shot Object Detection and Instance Segmentation

NEURIPS 2022arXiv

citations

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

ICLR 2025arXiv

citations

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

AAAI 2024

citations

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

CVPR 2025

citations

MatchDet: A Collaborative Framework for Image Matching and Object Detection

AAAI 2024arXiv

citations

Bin-Bin Gao

papers (10)

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

Unsupervised Continual Anomaly Detection with Contrastively-Learned Prompt

Decoupling Classifier for Boosting Few-shot Object Detection and Instance Segmentation

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

tSF: Transformer-Based Semantic Filter for Few-Shot Learning

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

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

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

MatchDet: A Collaborative Framework for Image Matching and Object Detection

papers (10)

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

Unsupervised Continual Anomaly Detection with Contrastively-Learned Prompt

Decoupling Classifier for Boosting Few-shot Object Detection and Instance Segmentation

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

tSF: Transformer-Based Semantic Filter for Few-Shot Learning

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

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

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

MatchDet: A Collaborative Framework for Image Matching and Object Detection