Official Review · NEURIPS 2024

This paper adopts a novel plug-and-play framework that reverses the generative process of face forgeries to enhance the generalization of detection models. Extensive experimental results from several datasets demonstrate that this method has achieved very competitive performance. - The motivation of this paper is clear and the approach to implementing it is straightforward and understandable. - This paper attempts to introduce Stable Diffusion into deepfake detection, unifying the generation model and the detection model end-to-end, which is very interesting and innovative, and provides a new perspective for this field. - The overall structure of this paper is relatively reasonable and the context of the paper is relatively clear. - Some recently published papers about enhancing generalization in deepfake detection are not cited and discussed, such as: [1] Dong, Shichao, et al. "Implicit identity leakage: The stumbling block to improving deepfake detection generalization." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2023. [2] Yu, Bingyao, et al. "Discrepancy-aware meta-learning for zero-shot face manipulation detection." IEEE Transactions on Image Processing (2023). [3] Chen, Liang, et al. "Self-supervised learning of adversarial example: Towards good generalizations for deepfake detection." Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2022. - Many of the experimental results in Table 1 provided by the authors in the paper are inconsistent with or may be lower than the experimental results in the original paper. It is best for the authors to provide detailed, clear and convincing explanations. - In order to better understand the performance of the proposed method, it would be best if the authors could provide sample visualization results of misprediction and give corresponding theoretical analysis. - Please unify the format of references. At least make sure that the reference formats of conferences and journals are consistent. - If the author can answer and revise the relevant questions in the final version, I will consider increasing the final score in the next round. Please standardize the capitalization of English letters in the references. Many abbreviations of proper nouns are incorrect, such as Aunet (AUNet).