| Deep Industrial Image Anomaly Detection: A Survey J Liu*, G Xie*, J Wang*, S Li, C Wang, F Zheng, Y Jin Machine Intelligence Research, 2024, 21(1): 104-135., 2023 | 69 | 2023 |
| Pushing the limits of fewshot anomaly detection in industry vision: Graphcore G Xie*, J Wang*, J Liu*, F Zheng, Y Jin The Eleventh International Conference on Learning Representations. 2023 …, 2023 | 41 | 2023 |
| Im-iad: Industrial image anomaly detection benchmark in manufacturing G Xie*, J Wang*, J Liu*, J Lyu, Y Liu, C Wang, F Zheng, Y Jin IEEE Transactions on Cybernetics, 2024., 2023 | 33 | 2023 |
| Real3D-AD: A Dataset of Point Cloud Anomaly Detection J Liu*, G Xie*, R Chen*, X Li, J Wang, Y Liu, C Wang, F Zheng Advances in Neural Information Processing Systems, 2023, 36. (NeurIPS 2023), 2023 | 15 | 2023 |
| EasyNet: An Easy Network for 3D Industrial Anomaly Detection R Chen*, G Xie*, J Liu*, J Wang, Z Luo, J Wang, F Zheng Proceedings of the 31st ACM International Conference on Multimedia. 2023 …, 2023 | 14 | 2023 |
| What makes a good data augmentation for few-shot unsupervised image anomaly detection? L Zhang*, S Zhang*, G Xie, J Liu, H Yan, J Wang, F Zheng, Y Jin Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 5 | 2023 |
| Unsupervised Continual Anomaly Detection with Contrastively-learned Prompt J Liu*, K Wu*, Q Nie, Y Chen, BB Gao, Y Liu, J Wang, C Wang, F Zheng Proceedings of the AAAI Conference on Artificial Intelligence, 38(4), 3639 …, 2024 | 1 | 2024 |
| Tuning-Free Adaptive Style Incorporation for Structure-Consistent Text-Driven Style Transfer Y Ge, J Liu, Q Fan, X Jiang, Y Huang, S Qin, H Gu, W Li, L Duan arXiv preprint arXiv:2404.06835, 2024 | | 2024 |
Feng ZhengSouthern University of Science and TechnologyVerified email at sustech.edu.cn
