Registration based few-shot anomaly detection C Huang, H Guan, A Jiang, Y Zhang, M Spratling, YF Wang European Conference on Computer Vision, 303-319, 2022 | 109 | 2022 |
One prompt word is enough to boost adversarial robustness for pre-trained vision-language models L Li, H Guan, J Qiu, M Spratling Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 8 | 2024 |
Rethinking the backbone architecture for tiny object detection J Ning, H Guan, M Spratling arXiv preprint arXiv:2303.11267, 2023 | 7 | 2023 |
Query semantic reconstruction for background in few-shot segmentation H Guan, M Spratling The Visual Computer 40 (2), 799-810, 2024 | 1 | 2024 |
Deep dual-view network with smooth loss for spinal metastases classification H Guan, G Yao, Y Zhang, Y Gu, H Zhao, Y Zhang, X Gu 2018 IEEE Visual Communications and Image Processing (VCIP), 1-4, 2018 | 1 | 2018 |
Few-Shot Anomaly Detection via Category-Agnostic Registration Learning C Huang, H Guan, A Jiang, Y Wang, M Spratling, X Wang, Y Zhang arXiv preprint arXiv:2406.08810, 2024 | | 2024 |
CobNet: Cross Attention on Object and Background for Few-Shot Segmentation H Guan, S Michael 2022 26th International Conference on Pattern Recognition (ICPR), 39-45, 2022 | | 2022 |
Supplementary Material for Registration based Few-Shot Anomaly Detection C Huang, H Guan, A Jiang, Y Zhang, M Spratling, YF Wang | | |