| UIA-ViT: Unsupervised inconsistency-aware method based on vision transformer for face forgery detection W Zhuang, Q Chu, Z Tan, Q Liu, H Yuan, C Miao, Z Luo, N Yu European Conference on Computer Vision, 391-407, 2022 | 44 | 2022 |
| Automa: Towards automatic model augmentation for transferable adversarial attacks H Yuan, Q Chu, F Zhu, R Zhao, B Liu, N Yu IEEE Transactions on Multimedia 25, 203-213, 2021 | 11 | 2021 |
| Towards intrinsic common discriminative features learning for face forgery detection using adversarial learning W Zhuang, Q Chu, H Yuan, C Miao, B Liu, N Yu 2022 IEEE International Conference on Multimedia and Expo (ICME), 1-6, 2022 | 8 | 2022 |
| Efficient open-set adversarial attacks on deep face recognition H Yuan, Q Chu, F Zhu, R Zhao, B Liu, N Yu 2021 IEEE International Conference on Multimedia and Expo (ICME), 1-6, 2021 | 2 | 2021 |
| Delving Deeper Into Vulnerable Samples in Adversarial Training P Zhao, H Yuan, Q Chu, S Xu, N Yu ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | | 2024 |
| Enhancing Adversarial Transferability from the Perspective of Input Loss Landscape Y Xu, Q Chu, H Yuan, Z Luo, B Liu, N Yu International Conference on Image and Graphics, 254-266, 2023 | | 2023 |
