| Automatic steganographic distortion learning using a generative adversarial network W Tang, S Tan, B Li, J Huang IEEE Signal Processing Letters 24 (10), 1547-1551, 2017 | 351 | 2017 |
| CNN-based adversarial embedding for image steganography W Tang, B Li, S Tan, M Barni, J Huang IEEE Transactions on Information Forensics and Security 14 (8), 2074-2087, 2019 | 276 | 2019 |
| Adaptive steganalysis against WOW embedding algorithm W Tang, H Li, W Luo, J Huang Proceedings of the 2nd ACM workshop on Information hiding and multimedia …, 2014 | 130 | 2014 |
| An automatic cost learning framework for image steganography using deep reinforcement learning W Tang, B Li, M Barni, J Li, J Huang IEEE Transactions on Information Forensics and Security 16, 952-967, 2020 | 125 | 2020 |
| Adaptive steganalysis based on embedding probabilities of pixels W Tang, H Li, W Luo, J Huang IEEE Transactions on Information Forensics and Security 11 (4), 734-745, 2015 | 106 | 2015 |
| Attacking deep reinforcement learning with decoupled adversarial policy K Mo, W Tang, J Li, X Yuan IEEE Transactions on Dependable and Secure Computing 20 (1), 758-768, 2022 | 63 | 2022 |
| Clustering steganographic modification directions for color components W Tang, B Li, W Luo, J Huang IEEE Signal Processing Letters 23 (2), 197-201, 2015 | 47 | 2015 |
| Improving cost learning for JPEG steganography by exploiting JPEG domain knowledge W Tang, B Li, M Barni, J Li, J Huang IEEE Transactions on Circuits and Systems for Video Technology 32 (6), 4081-4095, 2021 | 19 | 2021 |
| Image steganography based on iterative adversarial perturbations onto a synchronized-directions sub-image X Qin, S Tan, W Tang, B Li, J Huang ICASSP 2021-2021 IEEE international conference on acoustics, speech and …, 2021 | 19 | 2021 |
| Gradually enhanced adversarial perturbations on color pixel vectors for image steganography X Qin, B Li, S Tan, W Tang, J Huang IEEE Transactions on Circuits and Systems for Video Technology 32 (8), 5110-5123, 2022 | 15 | 2022 |
| ReLOAD: Using reinforcement learning to optimize asymmetric distortion for additive steganography X Mo, S Tan, W Tang, B Li, J Huang IEEE Transactions on Information Forensics and Security 18, 1524-1538, 2023 | 13 | 2023 |
| Privacy-Preserving Multi-Granular Federated Neural Architecture Search–A General Framework Z Pan, L Hu, W Tang, J Li, Y He, Z Liu IEEE Transactions on Knowledge and Data Engineering 35 (3), 2975-2986, 2021 | 12 | 2021 |
| Reinforcement learning of non-additive joint steganographic embedding costs with attention mechanism W Tang, B Li, W Li, Y Wang, J Huang Science China Information Sciences 66 (3), 132305, 2023 | 9 | 2023 |
| ‘CNN based adversarial embedding with minimum alteration for image steganography W Tang, B Li, S Tan, M Barni, J Huang arXiv preprint arXiv:1803.09043, 2018 | 5 | 2018 |
| Vulnerabilities in video quality assessment models: The challenge of adversarial attacks A Zhang, Y Ran, W Tang, YG Wang Advances in Neural Information Processing Systems 36, 2024 | 4 | 2024 |
| HVS revisited: A comprehensive video quality assessment framework AX Zhang, YG Wang, W Tang, L Li, S Kwong arXiv preprint arXiv:2210.04158, 2022 | 4 | 2022 |
| Content-adaptive steganalysis via augmented utilization of selection-channel information S Zhou, W Tang, S Tan, B Li International Workshop on Digital Watermarking, 261-274, 2018 | 4 | 2018 |
| A stealthy and robust backdoor attack via frequency domain transform R Hou, T Huang, H Yan, L Ke, W Tang World Wide Web 26 (5), 2767-2783, 2023 | 3 | 2023 |
| Anti-forensics for double JPEG compression based on generative adversarial network D Huang, W Tang, B Li International Conference on Image and Graphics, 759-771, 2021 | 3 | 2021 |
| Steganography Embedding Cost Learning with Generative Multi-Adversarial Network D Huang, W Luo, M Liu, W Tang, J Huang IEEE Transactions on Information Forensics and Security, 2023 | 2 | 2023 |
