Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T04:07:15.027658Z
Paper Citation Record · LEDGER
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes
As of 22 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 1 inbound Pith citation observation for arXiv:2506.11477.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-20T13:08:29.414406Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-20T13:13:18.677212Z
Reference resolution
57 of 57 outbound references displayed
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 1ed8e3af-d44c-4f03-be56-406231489a92 · outbound
This paper cites Mesonet: A com- pact facial video forgery detection network.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Mesonet: A com- pact facial video forgery detection network
Reference 1
- Resolution
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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 6800bfca-7078-4912-95fd-199e049244df · outbound
This paper cites Detecting deep-fake videos from aural and oral dy- namics.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Detecting deep-fake videos from aural and oral dy- namics
Reference 2
- Resolution
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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 94666255-b57f-4947-84e9-9ef54fc67e5c · outbound
This paper cites Resvit: A framework for deepfake videos detection.International Journal of Electrical and Com- puter Engineering Systems, 13(9):807–813, 2022.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Resvit: A framework for deepfake videos detection.International Journal of Electrical and Com- puter Engineering Systems, 13(9):807–813, 2022
Reference 3
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Observation 60ba1fcc-da68-48e5-900e-9fb314f0611b · outbound
This paper cites Capst: Leveraging capsule networks and temporal attention for accurate model attribution in deep-fake videos.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Capst: Leveraging capsule networks and temporal attention for accurate model attribution in deep-fake videos
Reference 4
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Observation e034ab4c-b763-46a4-a0a1-1ceac0b93764 · outbound
This paper cites Vivit: A video vision transformer.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Vivit: A video vision transformer
Reference 5
- Resolution
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Source-reported events for the cited work
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Observation e84702e2-d060-4e4d-90d1-1fcd1f4ac9eb · outbound
This paper cites Reverse engineering of generative models: Inferring model hyperparameters from generated images.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Reverse engineering of generative models: Inferring model hyperparameters from generated images
Reference 6
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation f4f3fd68-c24c-4230-acae-7c538ebfa988 · outbound
This paper cites Openface 2.0: Facial behavior analysis toolkit.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Openface 2.0: Facial behavior analysis toolkit
Reference 7
- Resolution
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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation fc498362-c139-416c-8b84-e42836274f28 · outbound
This paper cites Is space-time attention all you need for video understanding? In Proceedings of the International Conference on Machine Learning (ICML), pages 813–824.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Is space-time attention all you need for video understanding? In Proceedings of the International Conference on Machine Learning (ICML), pages 813–824
Reference 8
- Resolution
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Source-reported events for the cited work
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Observation 9b6aa3b6-7d15-494d-bdac-2fbe6da070f3 · outbound
This paper cites Video face manipulation detection through ensemble of cnns.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Video face manipulation detection through ensemble of cnns
Reference 9
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Source-reported events for the cited work
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Observation ba41a17f-518e-4dd1-a9c4-19b13ab26084 · outbound
This paper cites How far are we from solving the 2d & 3d face alignment problem? (and a dataset of 230,000 3d facial landmarks).
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes How far are we from solving the 2d & 3d face alignment problem? (and a dataset of 230,000 3d facial landmarks)
Reference 10
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Source-reported events for the cited work
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Observation 36f3b3d7-b1eb-42ea-ab60-2454dcf6895a · outbound
This paper cites Neural head reen- actment with latent pose descriptors.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Neural head reen- actment with latent pose descriptors
Reference 11
- Resolution
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Source-reported events for the cited work
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Observation 629fe52d-79d6-4182-b51b-0b6eb1696ccf · outbound
This paper cites Deep fakes: A looming challenge for privacy, democracy, and national security.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Deep fakes: A looming challenge for privacy, democracy, and national security
Reference 12
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Source-reported events for the cited work
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Observation f0fa9557-c6b7-40f7-beaf-4389ed66d175 · outbound
This paper cites Xception: Deep learning with depthwise separable convolutions.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Xception: Deep learning with depthwise separable convolutions
Reference 13
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Observation ff8c0ef9-d687-4e68-8e38-ac350d343745 · outbound
This paper cites Deepfake detection using spatiotemporal convolutional networks.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Deepfake detection using spatiotemporal convolutional networks
Reference 14
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Source-reported events for the cited work
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Observation c5c6aff0-3091-4d47-a29a-badbc944079e · outbound
This paper cites an unresolved cited work.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Unresolved cited work
Reference 15
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Observation 970968e8-9620-45f5-833a-6f9af0cd5483 · outbound
This paper cites The deepfake detection challenge (dfdc) dataset.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes The deepfake detection challenge (dfdc) dataset
Reference 16
- Resolution
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Source-reported events for the cited work
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Observation 75e205af-b0ff-4684-b71b-5fda61e7b098 · outbound
This paper cites The deepfake detection challenge (dfdc) preview dataset.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes The deepfake detection challenge (dfdc) preview dataset
Reference 17
- Resolution
- verified fuzzy
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Source-reported events for the cited work
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Observation 10a3d887-f7c6-4408-bfa4-e34224b45d61 · outbound
This paper cites Unmasking deep- fakes with simple features.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Unmasking deep- fakes with simple features
Reference 18
- Resolution
- verified fuzzy
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Observation 8cd7a76a-d7e7-4253-87c0-22fe765dbd72 · outbound
This paper cites High-fidelity face manipulation with extreme poses and expressions.IEEE Transactions on Information Forensics and Security, 16:2218–2231, 2021.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes High-fidelity face manipulation with extreme poses and expressions.IEEE Transactions on Information Forensics and Security, 16:2218–2231, 2021
Reference 19
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Source-reported events for the cited work
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Observation d16e7e9e-47f6-43e5-b6ac-3710202d6ac3 · outbound
This paper cites Towards discovery and attribution of open-world gan generated images.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Towards discovery and attribution of open-world gan generated images
Reference 20
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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 0ffbf88e-6abc-462e-81af-1fe6253d7484 · outbound
This paper cites Accessed: Dec.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Accessed: Dec
Reference 21
- Resolution
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Source-reported events for the cited work
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Observation f8b2b205-799b-4b4b-a602-642fa3b726ec · outbound
This paper cites Accessed: Dec.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Accessed: Dec
Reference 22
- Resolution
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Source-reported events for the cited work
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Observation 0d806d4b-02ac-44a2-98e4-36ac0c2af5dd · outbound
This paper cites Spatiotemporal inconsistency learning for deepfake video detection.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Spatiotemporal inconsistency learning for deepfake video detection
Reference 23
- Resolution
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Source-reported events for the cited work
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Observation a09aa77e-55d4-4964-a7d2-e91aa9074f2e · outbound
This paper cites Deepfake detection by analyzing convolutional traces.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Deepfake detection by analyzing convolutional traces
Reference 24
- Resolution
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Source-reported events for the cited work
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Observation f74d0de6-6f3b-49aa-81cb-30c2bc29ee4b · outbound
This paper cites Multimodal forgery detection using ensemble learning.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Multimodal forgery detection using ensemble learning
Reference 25
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Source-reported events for the cited work
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Observation c1c2b7f5-82e0-4131-ba8a-8495b157a385 · outbound
This paper cites Deep residual learning for image recognition.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Deep residual learning for image recognition
Reference 26
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Observation ac78bdfd-8fdd-4715-be90-eaf9e69627fb · outbound
This paper cites Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, To- bias Weyand, Marco Andreetto, and Hartwig Adam.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, To- bias Weyand, Marco Andreetto, and Hartwig Adam
Reference 27
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Observation a766288d-f77e-41d2-8620-baa06906c8c5 · outbound
This paper cites Model attribution of face-swap deepfake videos.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Model attribution of face-swap deepfake videos
Reference 28
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Source-reported events for the cited work
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Observation 479cb5e4-a936-46cb-9fc7-d6f19122aa75 · outbound
This paper cites Deeperforensics- 1.0: A large-scale dataset for real-world face forgery detection.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Deeperforensics- 1.0: A large-scale dataset for real-world face forgery detection
Reference 29
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Observation aa382e75-7d77-4ff9-b25a-5d4ae8875105 · outbound
This paper cites Analyzing and improving the image quality of stylegan.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Analyzing and improving the image quality of stylegan
Reference 30
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Observation d84ace45-c65f-44e9-8b0f-23a77a42b21c · outbound
This paper cites an unresolved cited work.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Unresolved cited work
Reference 31
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Observation 064f6efc-00e0-43fa-8c46-53859ccaf87c · outbound
This paper cites an unresolved cited work.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Unresolved cited work
Reference 32
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Observation f1f666da-9f63-4cb7-b85e-5184aec63f73 · outbound
This paper cites Face x-ray for more general face forgery detection.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Face x-ray for more general face forgery detection
Reference 33
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Source-reported events for the cited work
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Observation 9479a0b4-d042-4bf1-b7b7-08add9161f0f · outbound
This paper cites Exposing deepfake videos by detecting face warping artifacts.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Exposing deepfake videos by detecting face warping artifacts
Reference 34
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 9c482b7e-6310-46e4-9cd3-fb93f67fb462 · outbound
This paper cites Exposing deepfake videos by detecting face warping artifacts.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Exposing deepfake videos by detecting face warping artifacts
Reference 35
- Resolution
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Source-reported events for the cited work
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Observation 3e31498c-e55a-4c6e-88e3-0433a2e68dbf · outbound
This paper cites Celeb-df: A large-scale challenging dataset for deepfake forensics.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Celeb-df: A large-scale challenging dataset for deepfake forensics
Reference 36
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 8c31ca27-5589-4363-acd8-3317f85aced9 · outbound
This paper cites Video swin transformer.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Video swin transformer
Reference 37
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 7c4cc786-3f01-40aa-80e8-2a845ad6f3f4 · outbound
This paper cites Deepfake detection: Current challenges and next steps.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Deepfake detection: Current challenges and next steps
Reference 38
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation b6b71770-5ab8-4634-8644-ee4e351d711e · outbound
This paper cites Do gans leave artificial fingerprints? In 2019 IEEE Conference on Multimedia Information Pro- cessing and Retrieval (MIPR), pages 506–511.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Do gans leave artificial fingerprints? In 2019 IEEE Conference on Multimedia Information Pro- cessing and Retrieval (MIPR), pages 506–511
Reference 39
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation ff242731-e9dc-48f6-9c3d-a2a4c6c31ab1 · outbound
This paper cites Two-branch recurrent network for isolating deepfakes in videos.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Two-branch recurrent network for isolating deepfakes in videos
Reference 40
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 897d01c5-f731-4232-ad52-cf7df96bb57a · outbound
This paper cites Frame attention networks for facial expression recognition in videos.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Frame attention networks for facial expression recognition in videos
Reference 41
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation c1ecbfd2-987e-44a9-a606-c7b32e338cb9 · outbound
This paper cites Emotions don’t lie: An audio-visual deepfake detection method using affective cues.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Emotions don’t lie: An audio-visual deepfake detection method using affective cues
Reference 42
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 32e4a1f7-f2ef-4fcb-92cb-fe83cf9e5f53 · outbound
This paper cites Nguyen, Junichi Yamagishi, and Isao Echizen.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Nguyen, Junichi Yamagishi, and Isao Echizen
Reference 43
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 3c5585f5-de76-4ba1-8ec4-88bf2c99b085 · outbound
This paper cites Use of attentional warping for low- resolution deepfake detection.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Use of attentional warping for low- resolution deepfake detection
Reference 44
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 6bad03fa-e53f-4fd9-8d05-367edffe4cad · outbound
This paper cites Deepfacelab: Integrated, flexible and extensible face-swapping framework.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Deepfacelab: Integrated, flexible and extensible face-swapping framework
Reference 45
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- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 63036286-8f67-4676-bd85-b500945d0b70 · outbound
This paper cites Faceforensics++: Learning to detect manipulated facial images.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Faceforensics++: Learning to detect manipulated facial images
Reference 46
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- verified fuzzy
- raw_fallback, observed 2026-08-07T04:07:17.445810Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 129f28a4-c111-4b94-9321-99093ae2c9a4 · outbound
This paper cites Mobilenetv2: Inverted residuals and linear bottlenecks.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Mobilenetv2: Inverted residuals and linear bottlenecks
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:07:17.204221Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 3380e926-4f96-48fa-8917-466ed33516dc · outbound
This paper cites Parei- dolia face reenactment.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Parei- dolia face reenactment
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:07:17.013575Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 82724447-51cb-4c22-bd3a-6c92e08b7111 · outbound
This paper cites Efficientnet: Rethinking model scaling for convolutional neural networks.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Efficientnet: Rethinking model scaling for convolutional neural networks
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:07:16.823467Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 3d17632e-4c62-4c8f-974e-5cf6574dd9a3 · outbound
This paper cites Media forensics and deepfakes: an overview.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Media forensics and deepfakes: an overview
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:07:16.554142Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 1a87f733-511a-403f-b676-454328415c6e · outbound
This paper cites Forgerynir: Deep face forgery and detection in near-infrared scenario.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Forgerynir: Deep face forgery and detection in near-infrared scenario
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:07:16.288364Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 4e8911c4-fae4-46b9-9ff7-2d05eddedf27 · outbound
This paper cites Cbam: Convolu- tional block attention module.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Cbam: Convolu- tional block attention module
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:07:16.044880Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 2ce9886e-50e5-4601-b02c-c415ddaef795 · outbound
This paper cites Facecontroller: Controllable attribute editing for face in the wild.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Facecontroller: Controllable attribute editing for face in the wild
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:07:15.853719Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation edf8227c-fede-471d-ad8f-e26722a0af02 · outbound
This paper cites an unresolved cited work.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Unresolved cited work
Reference 54
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T04:07:15.681636Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation e2ad6248-7817-4c1f-bd8f-77a715088047 · outbound
This paper cites Multi-attentional deepfake detection.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Multi-attentional deepfake detection
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:07:15.508702Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation f4d5734b-3870-48c5-9afb-4513b42a9c34 · outbound
This paper cites One shot face swapping on megapixels.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes One shot face swapping on megapixels
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:07:15.339010Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 0e96fd61-1a08-4929-abe7-cdb73d42edaf · outbound
This paper cites Wilddeep- fake: A challenging real-world dataset for deepfake detection.
FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes Wilddeep- fake: A challenging real-world dataset for deepfake detection
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T04:07:15.198692Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Pith citing papers
Observation 60eaaa06-7c3f-4610-b965-0b90052bbc55 · inbound
Deepfake Detection in Social Media: A Temporal Artifact Analysis Using 3D Convolutional Neural Networks cites this paper.
Deepfake Detection in Social Media: A Temporal Artifact Analysis Using 3D Convolutional Neural Networks FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T13:13:18.678916Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.