PONE-D-25-07298STFANet: A Spatial and Temporal Feature Aggregation Network for Fake Face Detection in VideosPLOS ONE

Dear Dr. Yao,

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Oliver Giudice, Ph.D.

Academic Editor

PLOS ONE

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Additional Editor Comments:

This paper needs some heavy rewriting in order to improve clarity. Experimental setting and design are to be better described in order to achieve reproducibility. The solution is novel but the paper needs many improvements to be considered for publication. Please refer also to reviewer 1 comments that authors need to address.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This study contributes to the field by introducing a novel approach for detecting fake faces in videos, differing from existing methods by utilizing the STFANet framework. Unlike conventional techniques, STFANet leverages a dual-path structure, which enhances the extraction and integration of spatial and temporal features. However, several areas require improvement to strengthen the manuscript.

The dataset usage is described, but the division into training, validation, and test sets needs more clarity. The authors should specify the exact number of videos used for each set to ensure reproducibility. Additionally, the study does not sufficiently address how the model performs against different types of manipulated videos, such as face-swapping, lip synchronization inconsistencies, or other deepfake techniques. A more detailed evaluation in this regard would enhance the comprehensiveness of the study.

While the model’s performance is compared with other state-of-the-art methods, statistical significance tests are missing. Conducting tests such as t-tests, ANOVA, or Wilcoxon signed-rank tests would help determine whether the observed performance improvements are statistically meaningful. Furthermore, the manuscript contains minor typographical errors (e.g., “experimens” should be corrected to “experiments”), and the overall readability would benefit from proofreading.

The conclusion section should more explicitly highlight the key contributions of STFANet. The advantages over other approaches should be clearly articulated, and key numerical findings (e.g., AUC scores) should be included to reinforce the model’s effectiveness. Additionally, future research directions should be elaborated, particularly regarding areas for potential improvement and further testing.

The introduction effectively establishes the significance of deepfake detection, but the originality of the proposed method needs to be emphasized more clearly. A direct statement on how STFANet specifically addresses gaps in existing research (e.g., "Our method resolves X and Y issues by...") would enhance the clarity of the contribution.

Figure descriptions are sometimes insufficient, particularly in distinguishing between Figure 5 and Figure 6. The differences between these figures should be explicitly explained so that readers can better understand the model’s components and processing flow. Additionally, Table 7 compares both video-based and image-based detection models, yet this distinction is not made clear in the table title or caption. Indicating whether each approach is image-based or video-based would improve the clarity of the comparison.

Overall, the study presents a promising approach, but these revisions are necessary to enhance its clarity, scientific rigor, and reproducibility.

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Reviewer #1: No

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PONE-D-25-07298R1STFANet: A spatial and temporal feature aggregation network for fake face detection in videosPLOS ONE

Dear Dr. Yao,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

AE Comments: Update the comparison with recent works.

Please submit your revised manuscript by Nov 13 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

• A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
• A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
• An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Sohail Saif, Ph.D

Academic Editor

PLOS ONE

Journal Requirements:

If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise. 

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

Reviewer #4: (No Response)

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: (No Response)

Reviewer #3: Yes

Reviewer #4: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: (No Response)

Reviewer #3: Yes

Reviewer #4: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: (No Response)

Reviewer #3: Yes

Reviewer #4: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: (No Response)

Reviewer #3: Yes

Reviewer #4: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: Recommendation:

Accept with minor revisions (language polishing)

The manuscript is technically sound, well-structured, and presents a meaningful contribution to the field of fake video detection. The authors have adequately addressed the previously provided reviewer comments, and the experimental results are comprehensive and convincing. I recommend acceptance of the manuscript pending minor revisions, specifically related to language polishing to enhance clarity and readability.

Reviewer #3: I have reviewed the revised submission thoroughly and am satisfied with the amendments made. The authors have addressed the points raised in the initial review comprehensively.

Reviewer #4: The authors have adequately addressed the reviewers' comments from the first round, and their responses are well-articulated and satisfactory. Besides that, I have the following comment:

The comparison with state-of-the-art methods in Table 4 lacks recent works from 2024–2025. The same applies to Table 7.

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: No

Reviewer #3: No

Reviewer #4: No

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[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

Attachments

Attachment

Submitted filename: Recommendation.pdf

STFANet: A spatial and temporal feature aggregation network for fake face detection in videos

PONE-D-25-07298R2

Dear Dr. Yao,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Kind regards,

Sohail Saif, Ph.D

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments: