Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection | Paper Citation Record

Observation 43285ba1-b79a-47b7-8fff-581b2fcfaf13 · outbound

This paper cites Gpt-4 technical report.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Gpt-4 technical report

Reference 1

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Observation 031bb787-1da0-4bd9-b87c-a0f274d0de79 · outbound

This paper cites Mesonet: a compact facial video forgery detection network.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Mesonet: a compact facial video forgery detection network

Reference 2

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Observation 2ac247be-e9fb-4e08-a421-8d46455e81aa · outbound

This paper cites Limits of Deepfake Detection: A Robust Estimation Viewpoint.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Limits of Deepfake Detection: A Robust Estimation Viewpoint

Reference 3

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This paper cites Image forgery detection by trans- forming local descriptors into deep-derived features.Applied Soft Computing, 147:110730, 2023.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Image forgery detection by trans- forming local descriptors into deep-derived features.Applied Soft Computing, 147:110730, 2023

Reference 4

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Observation 0e2155ca-f9cd-4ee1-94ba-bbe9f2f09c3a · outbound

This paper cites Exposing the deception: Uncov- ering more forgery clues for deepfake detection.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Exposing the deception: Uncov- ering more forgery clues for deepfake detection

Reference 5

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Observation a65efc56-5c53-40e4-82ea-14a33c01e504 · outbound

This paper cites Zelensky told to leave white house after angry spat with trump and vance.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Zelensky told to leave white house after angry spat with trump and vance

Reference 6

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Observation c9a6b104-18c7-4a2c-900e-449af5cbd5bb · outbound

This paper cites End-to-end reconstruction- classification learning for face forgery detection.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection End-to-end reconstruction- classification learning for face forgery detection

Reference 7

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Observation 81128c25-1da0-44c8-8ea9-93f5fb35e5dd · outbound

This paper cites Unveiling the truth: Exploring human gaze patterns in fake images.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Unveiling the truth: Exploring human gaze patterns in fake images

Reference 8

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Observation 6897f914-38f1-4d16-baa8-3be4305c84f1 · outbound

This paper cites Role of human physiology and facial biomechanics towards building robust deepfake detectors: A comprehensive survey and analysis.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Role of human physiology and facial biomechanics towards building robust deepfake detectors: A comprehensive survey and analysis

Reference 9

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This paper cites Spar- tan: Self-supervised spatiotemporal transformers approach to group activity recognition.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Spar- tan: Self-supervised spatiotemporal transformers approach to group activity recognition

Reference 10

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Observation 54b640ee-c6e4-4c72-862e-fa8f8685ff07 · outbound

This paper cites Simswap: An efficient framework for high fidelity face swapping.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Simswap: An efficient framework for high fidelity face swapping

Reference 11

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Observation bf1d22dd-e84a-4ae5-94e5-83c928473923 · outbound

This paper cites Unsupervised outlier detection in appearance-based gaze es- timation.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Unsupervised outlier detection in appearance-based gaze es- timation

Reference 12

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Observation d17afa55-62ae-4270-989c-b967ff8f7d69 · outbound

This paper cites Exploiting style latent flows for generalizing deepfake video detection.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Exploiting style latent flows for generalizing deepfake video detection

Reference 13

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Observation 7e1d7ae6-a0ea-476a-8939-69c50d19d655 · outbound

This paper cites Fakecatcher: Detection of synthetic portrait videos using biological sig- nals.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Fakecatcher: Detection of synthetic portrait videos using biological sig- nals

Reference 14

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Observation f3e0923d-347b-404e-a462-8289162c5fd1 · outbound

This paper cites Evaluating amazon’s mechanical turk as a tool for experimental behavioral research.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Evaluating amazon’s mechanical turk as a tool for experimental behavioral research

Reference 15

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Observation 3d9feee1-7805-45dc-a8b5-a3393773d33f · outbound

This paper cites Body image: Gender, ethnic, and age differences.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Body image: Gender, ethnic, and age differences

Reference 16

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Observation a1c04e34-0176-4d7d-85c9-dbcd642faf3b · outbound

This paper cites The DeepFake Detection Challenge (DFDC) Dataset.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection The DeepFake Detection Challenge (DFDC) Dataset

Reference 17

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Observation 0d2107b7-62ea-4004-8d10-64fb270860dd · outbound

This paper cites Human per- ception of visual realism for photo and computer-generated face images.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Human per- ception of visual realism for photo and computer-generated face images

Reference 18

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Observation 60d9f5ad-5940-478f-850a-e1c82859a03f · outbound

This paper cites What is” special” about face perception? Psychological review, 105(3):482, 1998.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection What is” special” about face perception? Psychological review, 105(3):482, 1998

Reference 19

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Observation c57093b2-02b4-4b46-8747-2388b042b3bd · outbound

This paper cites Creating, using, misusing, and detecting deep fakes.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Creating, using, misusing, and detecting deep fakes

Reference 20

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Observation 0cdf2fa4-e137-49ba-9584-2a1f373464c6 · outbound

This paper cites Recognition of images de- graded by gaussian blur.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Recognition of images de- graded by gaussian blur

Reference 21

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This paper cites Social belonging motivates categoriza- tion of racially ambiguous faces.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Social belonging motivates categoriza- tion of racially ambiguous faces

Reference 22

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Observation 17bdb8e3-d5fa-466e-9cb0-f14a97f988dd · outbound

This paper cites Understanding im- ages of groups of people.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Understanding im- ages of groups of people

Reference 23

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Observation 48002894-32d9-433a-a678-a1919aa43a86 · outbound

This paper cites Automatic gaze analysis: A survey of deep learning based approaches.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Automatic gaze analysis: A survey of deep learning based approaches

Reference 24

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Observation d17c4a02-bf36-482c-8d9b-33afc129441a · outbound

This paper cites Delving into the local: Dynamic in- consistency learning for deepfake video detection.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Delving into the local: Dynamic in- consistency learning for deepfake video detection

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.546923Z

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Observation 3f5754d4-f325-4a8b-beb9-06da0e54da2f · outbound

This paper cites Exploring Spatial-Temporal Features for Deepfake Detection and Localization.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Exploring Spatial-Temporal Features for Deepfake Detection and Localization

Reference 26

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Observation a9780ab1-378a-4c0e-926c-908ead90f78b · outbound

This paper cites Lips don’t lie: A generalisable and robust approach to face forgery detection.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Lips don’t lie: A generalisable and robust approach to face forgery detection

Reference 27

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Observation 1cb1a2f1-9a10-428d-b73f-49fa20365c71 · outbound

This paper cites Haxby, Elizabeth A.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Haxby, Elizabeth A

Reference 28

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Observation efc5f9b1-b301-42ef-9b83-77b6f7591244 · outbound

This paper cites Deep residual learning for image recognition.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Deep residual learning for image recognition

Reference 29

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This paper cites Mask r-cnn.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Mask r-cnn

Reference 30

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Observation 712f6779-bb27-4b52-b176-13d9305259d8 · outbound

This paper cites How does gaze to faces support face-to-face interaction? a review and perspective.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection How does gaze to faces support face-to-face interaction? a review and perspective

Reference 31

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Observation a11d1fbf-5437-4214-a15d-5a42ac398a73 · outbound

This paper cites Detecting compressed deepfake videos in social networks using frame- temporality two-stream convolutional network.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Detecting compressed deepfake videos in social networks using frame- temporality two-stream convolutional network

Reference 32

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Observation 5ebcf894-7ca6-4f4a-9917-99ea0850ba67 · outbound

This paper cites A hierarchical deep temporal model for group activity recognition.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection A hierarchical deep temporal model for group activity recognition

Reference 33

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Observation 98059143-af6b-4564-8376-c503ec923d49 · outbound

This paper cites Double face: Leveraging user intelligence to characterize and recognize ai-synthesized faces.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Double face: Leveraging user intelligence to characterize and recognize ai-synthesized faces

Reference 34

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This paper cites Domain specificity in face perception.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Domain specificity in face perception

Reference 35

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Observation 2d579ffa-3173-44b7-a7d0-7562e6128d49 · outbound

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Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Unresolved cited work

Reference 36

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This paper cites Can you all look here? towards determining gaze uniformity in group images.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Can you all look here? towards determining gaze uniformity in group images

Reference 37

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Observation b8c79186-00cd-4b6e-be38-408e049b1511 · outbound

This paper cites Do the eyes have it? cues to the direction of social attention.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Do the eyes have it? cues to the direction of social attention

Reference 38

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Observation ab21a7fc-7502-4c97-89c9-f8b6ec751271 · outbound

This paper cites Openforensics: Large-scale challenging dataset for multi-face forgery detection and segmentation in- the-wild.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Openforensics: Large-scale challenging dataset for multi-face forgery detection and segmentation in- the-wild

Reference 39

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This paper cites FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping

Reference 40

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Observation 911ee9bf-7505-4a91-9de7-c3c95d698ad3 · outbound

This paper cites Sharp mul- tiple instance learning for deepfake video detection.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Sharp mul- tiple instance learning for deepfake video detection

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.456737Z

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Observation 2ab8ba43-3d87-4ea3-8e55-a971b75aef03 · outbound

This paper cites Exposing Deepfake videos by detecting face warping artifacts.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Exposing Deepfake videos by detecting face warping artifacts

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.448888Z

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Observation 9b753392-32e0-407c-af1d-3d6373c0a488 · outbound

This paper cites Exploiting facial relationships and feature aggregation for multi-face forgery detection.TIFS, 19:8832– 8844, 2024.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Exploiting facial relationships and feature aggregation for multi-face forgery detection.TIFS, 19:8832– 8844, 2024

Reference 43

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Observation 713cf926-b060-4dd3-9fb9-14184cc299ba · outbound

This paper cites Preserving fairness generalization in deepfake detection.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Preserving fairness generalization in deepfake detection

Reference 44

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Observation 54100b3f-7b8b-4bc9-bb81-5a9f20f90e70 · outbound

This paper cites Spatial- phase shallow learning: rethinking face forgery detection in frequency domain.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Spatial- phase shallow learning: rethinking face forgery detection in frequency domain

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.427740Z

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Observation d24418c5-5aad-479b-aeb8-ae8c78fd566e · outbound

This paper cites Exposingaicreated fakevideosbydetectingeyeblinking.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Exposingaicreated fakevideosbydetectingeyeblinking

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.420548Z

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Observation 487d580b-c2ab-45e9-8779-2b99b0ae799a · outbound

This paper cites Accurate and time-saving deepfake detection in multi-face scenarios using combined features.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Accurate and time-saving deepfake detection in multi-face scenarios using combined features

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.414033Z

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Observation 4828e79d-b6b0-41d6-b7e8-f5d58763319c · outbound

This paper cites Two- branch recurrent network for isolating deepfakes in videos.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Two- branch recurrent network for isolating deepfakes in videos

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.407436Z

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Observation 60c818f9-348f-419d-ba5a-390cb611bed5 · outbound

This paper cites Ex- ploiting visual artifacts to expose deepfakes and face manip- ulations.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Ex- ploiting visual artifacts to expose deepfakes and face manip- ulations

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.400874Z

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Observation 69e5593a-8ab3-4376-8416-2d7958f629b2 · outbound

This paper cites Mixture-of-Noises Enhanced Forgery-Aware Predictor for Multi-Face Manipulation Detection and Localization.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Mixture-of-Noises Enhanced Forgery-Aware Predictor for Multi-Face Manipulation Detection and Localization

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-08-06T15:52:39.050435Z

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Observation f0d2fdcb-c9d0-4e69-91af-a6610ec95d70 · outbound

This paper cites I hardly lie: A multistage fake news de- tection system.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection I hardly lie: A multistage fake news de- tection system

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.394094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 807c55fb-dc9c-41e4-91dc-a95f8621c6be · outbound

This paper cites Emotions don’t lie: An audio- visual deepfake detection method using affective cues.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Emotions don’t lie: An audio- visual deepfake detection method using affective cues

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.387581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6275d2cc-11ee-43d4-bec4-eda7b7484ba3 · outbound

This paper cites Df-platter: Multi- face heterogeneous deepfake dataset.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Df-platter: Multi- face heterogeneous deepfake dataset

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.381083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5ae21d38-9e49-4f57-a8eb-c842e755e5dc · outbound

This paper cites Nightingale and Hany Farid.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Nightingale and Hany Farid

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.374415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d7c05f46-dd14-4fec-8ab2-0b6f23900783 · outbound

This paper cites Fsgan: Subject agnostic face swapping and reenactment.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Fsgan: Subject agnostic face swapping and reenactment

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.368167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1c722ae9-f5be-4e9b-ab5d-1e790ca892a0 · outbound

This paper cites Deepfakes in video group.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Deepfakes in video group

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.360888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d2275555-1e71-410f-989b-054b038252da · outbound

This paper cites Pudd: Towards robust multi-modal prototype-based deepfake de- tection.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Pudd: Towards robust multi-modal prototype-based deepfake de- tection

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.354456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b568a0c0-4fef-46b0-9e73-2e26721c57df · outbound

This paper cites DeepFaceLab: Integrated, flexible and extensible face-swapping framework.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection DeepFaceLab: Integrated, flexible and extensible face-swapping framework

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-06T15:52:38.953715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c97e7bf-29bf-4e05-be52-71836a7ff204 · outbound

This paper cites Adversarial latent autoencoders.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Adversarial latent autoencoders

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.347963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 61f49669-3359-4bdb-85aa-ac2b025cdd75 · outbound

This paper cites Thinking in frequency: Face forgery detection by min- ing frequency-aware clues.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Thinking in frequency: Face forgery detection by min- ing frequency-aware clues

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.341513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a32f7fda-7581-47ac-9da4-5af46c002c0c · outbound

This paper cites Age and gender recog- nition in the wild with deep attention.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Age and gender recog- nition in the wild with deep attention

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.335092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9f861841-762d-495d-a5d6-c7bb4f121fc2 · outbound

This paper cites Faceforen- sics++: Learning to detect manipulated facial images.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Faceforen- sics++: Learning to detect manipulated facial images

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.247664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 04a5fb10-6c25-4ba8-9d56-1c070d18c5f7 · outbound

This paper cites Dex: Deep expectation of apparent age from a single image.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Dex: Deep expectation of apparent age from a single image

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.241014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9c8872f2-4fca-41dd-a56c-e4de9c3890d1 · outbound

This paper cites A review of driver gaze estimation and application in gaze behavior understanding.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection A review of driver gaze estimation and application in gaze behavior understanding

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.234334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b263a637-d08f-42a0-a7ae-6d1c4fa1bd17 · outbound

This paper cites Scale-aware cnn for crowd density estimation and crowd behavior analysis.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Scale-aware cnn for crowd density estimation and crowd behavior analysis

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.226959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e513a4cf-f907-48a6-96ab-12038270ced7 · outbound

This paper cites Spatio-temporal graph representation learning for fraudster group detection.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Spatio-temporal graph representation learning for fraudster group detection

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.220100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2fe4ed5c-4378-466b-b8c0-7318183bca0f · outbound

This paper cites Inter- preting the latent space of gans for semantic face editing.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Inter- preting the latent space of gans for semantic face editing

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.213016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 80d25efb-b3e8-4db3-a1e2-92858edabfae · outbound

This paper cites Detecting deep- fakes with self-blended images.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Detecting deep- fakes with self-blended images

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.206264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1192cc85-cbe7-4c22-9e65-c859b4151055 · outbound

This paper cites Gaze locking: passive eye contact detection for human- object interaction.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Gaze locking: passive eye contact detection for human- object interaction

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.198231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bb09780b-f39c-4902-971b-63573e28a3e5 · outbound

This paper cites Deepfake video detection via facial action dependencies estimation.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Deepfake video detection via facial action dependencies estimation

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.190359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3c13aa4d-5163-4e5b-ad3a-a62f13d5088a · outbound

This paper cites Illumination enlightened spatial-temporal inconsistency for deepfake video detection.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Illumination enlightened spatial-temporal inconsistency for deepfake video detection

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.182819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d4ab9ad3-a6c6-48e2-b25c-2bb4d06c066d · outbound

This paper cites Fake ai videos about trump fights with zelenskyy.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Fake ai videos about trump fights with zelenskyy

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.175785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 55f785ed-67f5-4c60-ae10-b83d5c4930a1 · outbound

This paper cites Attention is all you need.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Attention is all you need

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.168186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5027300c-ce0b-4a82-bae3-bbe5769cadf8 · outbound

This paper cites Pixel-wise crowd understanding via synthetic data.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Pixel-wise crowd understanding via synthetic data

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.160444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9e45288d-533d-4300-a770-6016c56f3518 · outbound

This paper cites Noise based deepfake de- tection via multi-head relative-interaction.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Noise based deepfake de- tection via multi-head relative-interaction

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.153671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bc570159-99f1-4fab-9948-4e0097777159 · outbound

This paper cites Gender and age classification of human faces for automatic detection of anomalous human behaviour.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Gender and age classification of human faces for automatic detection of anomalous human behaviour

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.146682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 556c20dd-99c2-4dd2-8386-d451389122a2 · outbound

This paper cites Deepfake on face and expression swap: A review.IEEE Access, 11:117865–117906, 2023.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Deepfake on face and expression swap: A review.IEEE Access, 11:117865–117906, 2023

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.139668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 31c85dd5-c01f-4c74-abee-fd7ad67d1cb7 · outbound

This paper cites Active factor graph network for group activity recog- nition.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Active factor graph network for group activity recog- nition

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.132400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7112ba8f-2eda-435a-879a-a24dfcbbc0c5 · outbound

This paper cites Tall: Thumbnail layout for deepfake video detection.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Tall: Thumbnail layout for deepfake video detection

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.125427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation cf15fcca-5be3-4681-951c-204d02de2a15 · outbound

This paper cites Spatio-temporal dynamic inference network for group activity recognition.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Spatio-temporal dynamic inference network for group activity recognition

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.118353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 606711ca-1043-4f2c-b3ad-255b08b4b429 · outbound

This paper cites Comics: End-to-end bi-grained contrastive learn- ing for multi-face forgery detection.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Comics: End-to-end bi-grained contrastive learn- ing for multi-face forgery detection

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.110675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6b4ec1f5-90b3-4c17-8864-b9e6fbf2b9d3 · outbound

This paper cites Gazeonce: Real- time multi-person gaze estimation.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Gazeonce: Real- time multi-person gaze estimation

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.103429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fad85376-d637-4018-bda1-221822d3f35c · outbound

This paper cites Two-stream neural networks for tampered face detection.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Two-stream neural networks for tampered face detection

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.096363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 557c80e2-4d62-462a-9004-2abf60d93315 · outbound

This paper cites Face forensics in the wild.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Face forensics in the wild

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.088995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4c817ac6-48c9-42b1-a0b0-b89123e34a21 · outbound

This paper cites Muggle: Multi-stream group gaze learning and estimation.

Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Muggle: Multi-stream group gaze learning and estimation

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:52:39.081679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Reference resolution

Outbound references

Pith citing papers