| Anomalygpt: Detecting industrial anomalies using large vision-language models Z Gu, B Zhu, G Zhu, Y Chen, M Tang, J Wang Proceedings of the AAAI Conference on Artificial Intelligence 38 (3), 1932-1940, 2024 | 101 | 2024 |
| Filo: Zero-shot anomaly detection by fine-grained description and high-quality localization Z Gu, B Zhu, G Zhu, Y Chen, H Li, M Tang, J Wang Proceedings of the 32nd ACM International Conference on Multimedia, 2041-2049, 2024 | 13 | 2024 |
| ADFormer: Generalizable Few-Shot Anomaly Detection with Dual CNN-Transformer Architecture B Zhu, Z Gu, G Zhu, Y Chen, M Tang, J Wang IEEE Transactions on Instrumentation and Measurement, 2024 | 1 | 2024 |
| FiLo++: Zero-/Few-Shot Anomaly Detection by Fused Fine-Grained Descriptions and Deformable Localization Z Gu, B Zhu, G Zhu, Y Chen, M Tang, J Wang arXiv preprint arXiv:2501.10067, 2025 | | 2025 |
| UniVAD: A Training-free Unified Model for Few-shot Visual Anomaly Detection Z Gu, B Zhu, G Zhu, Y Chen, M Tang, J Wang arXiv preprint arXiv:2412.03342, 2024 | | 2024 |
Jinqiao Wang 王金桥Professor, Institute of Automation,Chinese Academy of ScienceVerified email at nlpr.ia.ac.cn