| Spatiotemporal inconsistency learning for deepfake video detection Z Gu, Y Chen, T Yao, S Ding, J Li, F Huang, L Ma Proceedings of the 29th ACM international conference on multimedia, 3473-3481, 2021 | 141 | 2021 |
| A novel retinex-based fractional-order variational model for images with severely low light Z Gu, F Li, F Fang, G Zhang IEEE Transactions on Image Processing 29, 3239-3253, 2019 | 97 | 2019 |
| Delving into the local: Dynamic inconsistency learning for deepfake video detection Z Gu, Y Chen, T Yao, S Ding, J Li, L Ma Proceedings of the AAAI Conference on Artificial Intelligence 36 (1), 744-752, 2022 | 86 | 2022 |
| Hierarchical contrastive inconsistency learning for deepfake video detection Z Gu, T Yao, Y Chen, S Ding, L Ma European Conference on Computer Vision, 596-613, 2022 | 37 | 2022 |
| Towards artistic image aesthetics assessment: a large-scale dataset and a new method R Yi, H Tian, Z Gu, YK Lai, PL Rosin Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 30 | 2023 |
| Remembering normality: Memory-guided knowledge distillation for unsupervised anomaly detection Z Gu, L Liu, X Chen, R Yi, J Zhang, Y Wang, C Wang, A Shu, G Jiang, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 29 | 2023 |
| A detail preserving variational model for image Retinex Z Gu, F Li, XG Lv Applied Mathematical Modelling 68, 643-661, 2019 | 26 | 2019 |
| Real-iad: A real-world multi-view dataset for benchmarking versatile industrial anomaly detection C Wang, W Zhu, BB Gao, Z Gan, J Zhang, Z Gu, S Qian, M Chen, L Ma Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 23 | 2024 |
| Region-Aware Temporal Inconsistency Learning for DeepFake Video Detection. Z Gu, T Yao, Y Chen, R Yi, S Ding, L Ma IJCAI, 920-926, 2022 | 23 | 2022 |
| Rethinking Reverse Distillation for Multi-Modal Anomaly Detection Z Gu, J Zhang, L Liu, X Chen, J Peng, Z Gan, G Jiang, A Shu, Y Wang, ... Proceedings of the AAAI Conference on Artificial Intelligence 38 (8), 8445-8453, 2024 | 7 | 2024 |
| Prototype-Aware Contrastive Knowledge Distillation for Few-Shot Anomaly Detection. Z Gu, T Yang, L Ma BMVC, 259-263, 2023 | 2 | 2023 |
| CPSAM: Channel and Position Squeeze Attention Module Y Gong, Z Gu, Z Zhang, L Ma International Conference on Neural Information Processing, 190-202, 2021 | 1 | 2021 |
| Determining inconsistency of local motion to detect edited video GU Zhihao, YAO Taiping, Y Chen, D Shouhong US Patent App. 18/593,523, 2024 | | 2024 |
| Prototype-Aware Contrastive Knowledge Distillation for Few-Shot Anomaly Detection–The Supplementary Material Z Gu, L Ma, T Yang | | 2023 |
| Supplementary Materials for Real-IAD: A Real-World Multi-View Dataset for Benchmarking Versatile Industrial Anomaly Detection C Wang, W Zhu, BB Gao, Z Gan, J Zhang, Z Gu, S Qian, M Chen, L Ma | | |
| 基于风格记忆的跨域小样本异常检测 杨太海， 顾智浩， 马利庄 计算机辅助设计与图形学学报, 0 | | |
| Towards Artistic Image Aesthetics Assessment: a Large-scale Dataset and a New Method (Supplementary Material) R Yi, H Tian, Z Gu, Y Lai, PL Rosin | | |
