{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/face-swapping/papers/9","list_of":"/task/face-swapping","task":"Face Swapping","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":9,"pages_in_order":10,"rows_per_page":100,"rows":[801,900],"of":914,"counts":{"archive_papers_tagged":914,"with_a_code_link":342,"where_syntology_ran_a_sample":83,"not_listed_spam_title":0,"listed":914,"listed_where_code_ran":83,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":68,"every_run_a_failure_of_syntologys_instrument":15,"listed_with_a_run_with_no_instrument_failure":68,"listed_every_run_a_failure_of_syntologys_instrument":15,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/face-swapping","prev":"/task/face-swapping/papers/8","next":"/task/face-swapping/papers/10","papers":[{"url":null,"slug":"deepfake-detection-for-facial-images-with","title":"Deepfake Detection for Facial Images with Facemasks","date":"2022-02-23","arxiv_id":"2202.11359","repositories_listed":0,"syntology":null},{"url":null,"slug":"seeing-is-living-rethinking-the-security-of","title":"Seeing is Living? Rethinking the Security of Facial Liveness Verification in the Deepfake Era","date":"2022-02-22","arxiv_id":"2202.10673","repositories_listed":0,"syntology":null},{"url":null,"slug":"add-2022-the-first-audio-deep-synthesis","title":"ADD 2022: the First Audio Deep Synthesis Detection Challenge","date":"2022-02-17","arxiv_id":"2202.08433","repositories_listed":0,"syntology":null},{"url":null,"slug":"robust-deepfake-on-unrestricted-media","title":"Robust Deepfake On Unrestricted Media: Generation And Detection","date":"2022-02-13","arxiv_id":"2202.06228","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-review-of-deep-learning-based-approaches","title":"A Review of Deep Learning-based Approaches for Deepfake Content Detection","date":"2022-02-12","arxiv_id":"2202.06095","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-adversarially-robust-deepfake","title":"D4: Detection of Adversarial Diffusion Deepfakes Using Disjoint Ensembles","date":"2022-02-11","arxiv_id":"2202.05687","repositories_listed":0,"syntology":null},{"url":null,"slug":"frepgan-robust-deepfake-detection-using","title":"FrePGAN: Robust Deepfake Detection Using Frequency-level Perturbations","date":"2022-02-07","arxiv_id":"2202.03347","repositories_listed":0,"syntology":null},{"url":null,"slug":"crowd-powered-face-manipulation-detection","title":"Crowd-powered Face Manipulation Detection: Fusing Human Examiner Decisions","date":"2022-01-31","arxiv_id":"2201.13084","repositories_listed":0,"syntology":null},{"url":null,"slug":"psychophysical-evaluation-of-human","title":"Psychophysical Evaluation of Human Performance in Detecting Digital Face Image Manipulations","date":"2022-01-28","arxiv_id":"2201.12084","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepfake-disrupter-the-detector-of-deepfake","title":"DeepFake Disrupter: The Detector of DeepFake Is My Friend","date":"2022-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"smooth-swap-a-simple-enhancement-for-face","title":"Smooth-Swap: A Simple Enhancement for Face-Swapping with Smoothness","date":"2021-12-11","arxiv_id":"2112.05907","repositories_listed":0,"syntology":null},{"url":null,"slug":"physics-guided-deep-learning-generative","title":"Physics guided deep learning generative models for crystal materials discovery","date":"2021-12-07","arxiv_id":"2112.03528","repositories_listed":0,"syntology":null},{"url":null,"slug":"audio-deepfake-perceptions-in-college-going","title":"Audio Deepfake Perceptions in College Going Populations","date":"2021-12-06","arxiv_id":"2112.03351","repositories_listed":0,"syntology":null},{"url":null,"slug":"contrastive-learning-of-global-and-local-2","title":"Contrastive Learning of Global and Local Video Representations","date":"2021-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"how-deep-are-the-fakes-focusing-on-audio","title":"How Deep Are the Fakes? Focusing on Audio Deepfake: A Survey","date":"2021-11-28","arxiv_id":"2111.14203","repositories_listed":0,"syntology":null},{"url":null,"slug":"faketransformer-exposing-face-forgery-from","title":"FakeTransformer: Exposing Face Forgery From Spatial-Temporal Representation Modeled By Facial Pixel Variations","date":"2021-11-15","arxiv_id":"2111.07601","repositories_listed":0,"syntology":null},{"url":null,"slug":"impact-of-benign-modifications-on","title":"Impact of Benign Modifications on Discriminative Performance of Deepfake Detectors","date":"2021-11-14","arxiv_id":"2111.07468","repositories_listed":0,"syntology":null},{"url":null,"slug":"exposing-deepfake-with-pixel-wise-ar-and-ppg","title":"Exposing Deepfake with Pixel-wise AR and PPG Correlation from Faint Signals","date":"2021-10-29","arxiv_id":"2110.15561","repositories_listed":0,"syntology":null},{"url":null,"slug":"mc-lcr-multi-modal-contrastive-classification","title":"MC-LCR: Multi-modal contrastive classification by locally correlated representations for effective face forgery detection","date":"2021-10-07","arxiv_id":"2110.03290","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-experimental-evaluation-on-deepfake","title":"An Experimental Evaluation on Deepfake Detection using Deep Face Recognition","date":"2021-10-04","arxiv_id":"2110.01640","repositories_listed":0,"syntology":null},{"url":null,"slug":"video-forgery-detection-using-multiple-cues","title":"Video Forgery Detection Using Multiple Cues on Fusion of EfficientNet and Swin Transformer","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"machine-learning-based-medical-image-deepfake","title":"Machine Learning based Medical Image Deepfake Detection: A Comparative Study","date":"2021-09-27","arxiv_id":"2109.12800","repositories_listed":0,"syntology":null},{"url":null,"slug":"finding-facial-forgery-artifacts-with-parts","title":"Finding Facial Forgery Artifacts with Parts-Based Detectors","date":"2021-09-21","arxiv_id":"2109.10688","repositories_listed":0,"syntology":null},{"url":null,"slug":"md-csdnetwork-multi-domain-cross-stitched","title":"MD-CSDNetwork: Multi-Domain Cross Stitched Network for Deepfake Detection","date":"2021-09-15","arxiv_id":"2109.07311","repositories_listed":0,"syntology":null},{"url":null,"slug":"faceguard-proactive-deepfake-detection","title":"FaceGuard: Proactive Deepfake Detection","date":"2021-09-13","arxiv_id":"2109.05673","repositories_listed":0,"syntology":null},{"url":null,"slug":"detection-of-gan-synthesized-street-videos","title":"Detection of GAN-synthesized street videos","date":"2021-09-10","arxiv_id":"2109.04991","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepfakes-detecting-forged-and-synthetic","title":"DeepFakes: Detecting Forged and Synthetic Media Content Using Machine Learning","date":"2021-09-07","arxiv_id":"2109.02874","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluation-of-an-audio-video-multimodal","title":"Evaluation of an Audio-Video Multimodal Deepfake Dataset using Unimodal and Multimodal Detectors","date":"2021-09-07","arxiv_id":"2109.02993","repositories_listed":0,"syntology":null},{"url":null,"slug":"spatiotemporal-inconsistency-learning-for","title":"Spatiotemporal Inconsistency Learning for DeepFake Video Detection","date":"2021-09-04","arxiv_id":"2109.01860","repositories_listed":0,"syntology":null},{"url":null,"slug":"asvspoof-2021-accelerating-progress-in","title":"ASVspoof 2021: accelerating progress in spoofed and deepfake speech detection","date":"2021-09-01","arxiv_id":"2109.00537","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepfake-detection-with-inconsistent-head","title":"DeepFake Detection with Inconsistent Head Poses: Reproducibility and Analysis","date":"2021-08-28","arxiv_id":"2108.12715","repositories_listed":0,"syntology":null},{"url":null,"slug":"bihpf-bilateral-high-pass-filters-for-robust","title":"BiHPF: Bilateral High-Pass Filters for Robust Deepfake Detection","date":"2021-08-16","arxiv_id":"2109.00911","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepfake-representation-with-multilinear","title":"Deepfake Representation with Multilinear Regression","date":"2021-08-15","arxiv_id":"2108.06702","repositories_listed":0,"syntology":null},{"url":null,"slug":"unifacegan-a-unified-framework-for-temporally","title":"UniFaceGAN: A Unified Framework for Temporally Consistent Facial Video Editing","date":"2021-08-12","arxiv_id":"2108.05650","repositories_listed":0,"syntology":null},{"url":null,"slug":"video-transformer-for-deepfake-detection-with","title":"Video Transformer for Deepfake Detection with Incremental Learning","date":"2021-08-11","arxiv_id":"2108.05307","repositories_listed":0,"syntology":null},{"url":"/paper/openforensics-large-scale-challenging-dataset","slug":"openforensics-large-scale-challenging-dataset","title":"OpenForensics: Large-Scale Challenging Dataset For Multi-Face Forgery Detection And Segmentation In-The-Wild","date":"2021-07-30","arxiv_id":"2107.14480","repositories_listed":0,"syntology":null},{"url":null,"slug":"human-perception-of-audio-deepfakes","title":"Human Perception of Audio Deepfakes","date":"2021-07-20","arxiv_id":"2107.09667","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-systematical-solution-for-face-de","title":"A Systematical Solution for Face De-identification","date":"2021-07-19","arxiv_id":"2107.08581","repositories_listed":0,"syntology":null},{"url":null,"slug":"understanding-the-security-of-deepfake","title":"Understanding the Security of Deepfake Detection","date":"2021-07-05","arxiv_id":"2107.02045","repositories_listed":0,"syntology":null},{"url":null,"slug":"shapeediter-a-stylegan-encoder-for-face","title":"ShapeEditer: a StyleGAN Encoder for Face Swapping","date":"2021-06-26","arxiv_id":"2106.13984","repositories_listed":0,"syntology":null},{"url":null,"slug":"detection-of-deepfake-videos-using-long","title":"Detection of Deepfake Videos Using Long Distance Attention","date":"2021-06-24","arxiv_id":"2106.12832","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-deepfake-detection","title":"Automated Deepfake Detection","date":"2021-06-20","arxiv_id":"2106.10705","repositories_listed":0,"syntology":null},{"url":null,"slug":"imperceptible-adversarial-examples-for-fake","title":"Imperceptible Adversarial Examples for Fake Image Detection","date":"2021-06-03","arxiv_id":"2106.01615","repositories_listed":0,"syntology":null},{"url":null,"slug":"fretal-generalizing-deepfake-detection-using","title":"FReTAL: Generalizing Deepfake Detection using Knowledge Distillation and Representation Learning","date":"2021-05-28","arxiv_id":"2105.13617","repositories_listed":0,"syntology":null},{"url":null,"slug":"what-s-wrong-with-this-video-comparing","title":"What's wrong with this video? Comparing Explainers for Deepfake Detection","date":"2021-05-12","arxiv_id":"2105.05902","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-examination-of-fairness-of-ai-models-for","title":"An Examination of Fairness of AI Models for Deepfake Detection","date":"2021-05-02","arxiv_id":"2105.00558","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-insights-of-deepfake-technology-a-review","title":"Deep Insights of Deepfake Technology : A Review","date":"2021-05-01","arxiv_id":"2105.00192","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepfakeucl-deepfake-detection-via","title":"DeepfakeUCL: Deepfake Detection via Unsupervised Contrastive Learning","date":"2021-04-23","arxiv_id":"2104.11507","repositories_listed":0,"syntology":null},{"url":"/paper/towards-measuring-fairness-in-ai-the-casual","slug":"towards-measuring-fairness-in-ai-the-casual","title":"Towards Measuring Fairness in AI: the Casual Conversations Dataset","date":"2021-04-06","arxiv_id":"2104.02821","repositories_listed":0,"syntology":null},{"url":"/paper/kodf-a-large-scale-korean-deepfake-detection","slug":"kodf-a-large-scale-korean-deepfake-detection","title":"KoDF: A Large-scale Korean DeepFake Detection Dataset","date":"2021-03-18","arxiv_id":"2103.10094","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepfake-o-meter-an-open-platform-for","title":"DeepFake-o-meter: An Open Platform for DeepFake Detection","date":"2021-03-02","arxiv_id":"2103.02018","repositories_listed":0,"syntology":null},{"url":null,"slug":"am-i-a-real-or-fake-celebrity-measuring","title":"Am I a Real or Fake Celebrity? Measuring Commercial Face Recognition Web APIs under Deepfake Impersonation Attack","date":"2021-03-01","arxiv_id":"2103.00847","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepfakes-generation-and-detection-state-of","title":"Deepfakes Generation and Detection: State-of-the-art, open challenges, countermeasures, and way forward","date":"2021-02-25","arxiv_id":"2103.00484","repositories_listed":0,"syntology":null},{"url":"/paper/facecontroller-controllable-attribute-editing","slug":"facecontroller-controllable-attribute-editing","title":"FaceController: Controllable Attribute Editing for Face in the Wild","date":"2021-02-23","arxiv_id":"2102.11464","repositories_listed":0,"syntology":null},{"url":null,"slug":"adversarially-robust-deepfake-media-detection","title":"Adversarially robust deepfake media detection using fused convolutional neural network predictions","date":"2021-02-11","arxiv_id":"2102.05950","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-deepfake-detection-dilemma-a","title":"The Deepfake Detection Dilemma: A Multistakeholder Exploration of Adversarial Dynamics in Synthetic Media","date":"2021-02-11","arxiv_id":"2102.06109","repositories_listed":0,"syntology":null},{"url":null,"slug":"landmark-breaker-obstructing-deepfake-by","title":"Landmark Breaker: Obstructing DeepFake By Disturbing Landmark Extraction","date":"2021-02-01","arxiv_id":"2102.00798","repositories_listed":0,"syntology":null},{"url":null,"slug":"detecting-deepfake-videos-using-euler-video","title":"Detecting Deepfake Videos Using Euler Video Magnification","date":"2021-01-27","arxiv_id":"2101.11563","repositories_listed":0,"syntology":null},{"url":null,"slug":"fighting-deepfakes-by-detecting-gan-dct","title":"Fighting deepfakes by detecting GAN DCT anomalies","date":"2021-01-24","arxiv_id":"2101.09781","repositories_listed":0,"syntology":null},{"url":null,"slug":"bert-transformer-model-for-detecting-arabic","title":"BERT Transformer model for Detecting Arabic GPT2 Auto-Generated Tweets","date":"2021-01-22","arxiv_id":"2101.09345","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-adversarial-fake-images-on-face","title":"Exploring Adversarial Fake Images on Face Manifold","date":"2021-01-09","arxiv_id":"2101.03272","repositories_listed":0,"syntology":null},{"url":null,"slug":"fakebuster-a-deepfakes-detection-tool-for","title":"FakeBuster: A DeepFakes Detection Tool for Video Conferencing Scenarios","date":"2021-01-09","arxiv_id":"2101.03321","repositories_listed":0,"syntology":null},{"url":null,"slug":"contrastive-self-supervised-learning-of","title":"Contrastive Self-Supervised Learning of Global-Local Audio-Visual Representations","date":"2021-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/joint-audio-visual-deepfake-detection","slug":"joint-audio-visual-deepfake-detection","title":"Joint Audio-Visual Deepfake Detection","date":"2021-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"identifying-invariant-texture-violation-for","title":"Identifying Invariant Texture Violation for Robust Deepfake Detection","date":"2020-12-19","arxiv_id":"2012.10580","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-emerging-threats-of-deepfake-attacks-and","title":"The Emerging Threats of Deepfake Attacks and Countermeasures","date":"2020-12-14","arxiv_id":"2012.07989","repositories_listed":0,"syntology":null},{"url":null,"slug":"cost-sensitive-optimization-of-deepfake","title":"Cost Sensitive Optimization of Deepfake Detector","date":"2020-12-08","arxiv_id":"2012.04199","repositories_listed":0,"syntology":null},{"url":null,"slug":"identity-driven-deepfake-detection","title":"Identity-Driven DeepFake Detection","date":"2020-12-07","arxiv_id":"2012.03930","repositories_listed":0,"syntology":null},{"url":null,"slug":"adversarial-threats-to-deepfake-detection-a","title":"Adversarial Threats to DeepFake Detection: A Practical Perspective","date":"2020-11-19","arxiv_id":"2011.09957","repositories_listed":0,"syntology":null},{"url":null,"slug":"training-strategies-and-data-augmentations-in","title":"Training Strategies and Data Augmentations in CNN-based DeepFake Video Detection","date":"2020-11-16","arxiv_id":"2011.07792","repositories_listed":0,"syntology":null},{"url":null,"slug":"using-gans-to-synthesise-minimum-training","title":"Using GANs to Synthesise Minimum Training Data for Deepfake Generation","date":"2020-11-10","arxiv_id":"2011.05421","repositories_listed":0,"syntology":null},{"url":null,"slug":"spatio-temporal-features-for-generalized","title":"Spatio-temporal Features for Generalized Detection of Deepfake Videos","date":"2020-10-22","arxiv_id":"2010.11844","repositories_listed":0,"syntology":null},{"url":null,"slug":"fakeretouch-evading-deepfakes-detection-via","title":"Dodging DeepFake Detection via Implicit Spatial-Domain Notch Filtering","date":"2020-09-19","arxiv_id":"2009.09213","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepfake-detection-humans-vs-machines","title":"Deepfake detection: humans vs. machines","date":"2020-09-07","arxiv_id":"2009.03155","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepfake-detection-based-on-the-discrepancy","title":"DeepFake Detection Based on the Discrepancy Between the Face and its Context","date":"2020-08-27","arxiv_id":"2008.12262","repositories_listed":0,"syntology":null},{"url":null,"slug":"not-my-deepfake-towards-plausible-deniability","title":"On Attribution of Deepfakes","date":"2020-08-20","arxiv_id":"2008.09194","repositories_listed":0,"syntology":null},{"url":null,"slug":"exposing-deep-faked-videos-by-anomalous-co","title":"Exposing Deep-faked Videos by Anomalous Co-motion Pattern Detection","date":"2020-08-11","arxiv_id":"2008.04848","repositories_listed":0,"syntology":null},{"url":null,"slug":"sharp-multiple-instance-learning-for-deepfake","title":"Sharp Multiple Instance Learning for DeepFake Video Detection","date":"2020-08-11","arxiv_id":"2008.04585","repositories_listed":0,"syntology":null},{"url":null,"slug":"two-branch-recurrent-network-for-isolating","title":"Two-branch Recurrent Network for Isolating Deepfakes in Videos","date":"2020-08-08","arxiv_id":"2008.03412","repositories_listed":0,"syntology":null},{"url":null,"slug":"fighting-deepfake-by-exposing-the","title":"Fighting Deepfake by Exposing the Convolutional Traces on Images","date":"2020-08-07","arxiv_id":"2008.04095","repositories_listed":0,"syntology":null},{"url":null,"slug":"detecting-deepfake-videos-an-analysis-of","title":"Detecting Deepfake Videos: An Analysis of Three Techniques","date":"2020-07-15","arxiv_id":"2007.08517","repositories_listed":0,"syntology":null},{"url":null,"slug":"interpretable-deepfake-detection-via-dynamic","title":"Interpretable and Trustworthy Deepfake Detection via Dynamic Prototypes","date":"2020-06-28","arxiv_id":"2006.15473","repositories_listed":0,"syntology":null},{"url":null,"slug":"disrupting-deepfakes-with-an-adversarial","title":"OGAN: Disrupting Deepfakes with an Adversarial Attack that Survives Training","date":"2020-06-17","arxiv_id":"2006.12247","repositories_listed":0,"syntology":null},{"url":null,"slug":"deeprhythm-exposing-deepfakes-with","title":"DeepRhythm: Exposing DeepFakes with Attentional Visual Heartbeat Rhythms","date":"2020-06-13","arxiv_id":"2006.07634","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-face-preprocessing-approach-for-improved","title":"Investigating the Impact of Pre-processing and Prediction Aggregation on the DeepFake Detection Task","date":"2020-06-12","arxiv_id":"2006.07084","repositories_listed":0,"syntology":null},{"url":null,"slug":"defending-against-gan-based-deepfake-attacks","title":"Defending against GAN-based Deepfake Attacks via Transformation-aware Adversarial Faces","date":"2020-06-12","arxiv_id":"2006.07421","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-eyes-know-it-fakeet-an-eye-tracking","title":"The eyes know it: FakeET -- An Eye-tracking Database to Understand Deepfake Perception","date":"2020-06-12","arxiv_id":"2006.06961","repositories_listed":0,"syntology":null},{"url":null,"slug":"protecting-against-image-translation","title":"Protecting Against Image Translation Deepfakes by Leaking Universal Perturbations from Black-Box Neural Networks","date":"2020-06-11","arxiv_id":"2006.06493","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-note-on-deepfake-detection-with-low","title":"A Note on Deepfake Detection with Low-Resources","date":"2020-06-09","arxiv_id":"2006.05183","repositories_listed":0,"syntology":null},{"url":null,"slug":"advancing-high-fidelity-identity-swapping-for","title":"Advancing High Fidelity Identity Swapping for Forgery Detection","date":"2020-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"deepfake-forensics-using-recurrent-neural","title":"Deepfake Forensics Using Recurrent Neural Networks","date":"2020-05-01","arxiv_id":"2005.00229","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepfake-video-forensics-based-on-transfer","title":"Deepfake Video Forensics based on Transfer Learning","date":"2020-04-29","arxiv_id":"2004.14178","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepfakes-detection-with-automatic-face","title":"Deepfakes Detection with Automatic Face Weighting","date":"2020-04-25","arxiv_id":"2004.12027","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepfake-detection-by-analyzing-convolutional","title":"DeepFake Detection by Analyzing Convolutional Traces","date":"2020-04-22","arxiv_id":"2004.10448","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepfakes-evolution-analysis-of-facial","title":"DeepFakes Evolution: Analysis of Facial Regions and Fake Detection Performance","date":"2020-04-16","arxiv_id":"2004.07532","repositories_listed":0,"syntology":null},{"url":null,"slug":"evading-deepfake-image-detectors-with-white","title":"Evading Deepfake-Image Detectors with White- and Black-Box Attacks","date":"2020-04-01","arxiv_id":"2004.00622","repositories_listed":0,"syntology":null},{"url":null,"slug":"emotions-dont-lie-a-deepfake-detection-method","title":"Emotions Don't Lie: An Audio-Visual Deepfake Detection Method Using Affective Cues","date":"2020-03-14","arxiv_id":"2003.06711","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepfake-detection-current-challenges-and","title":"DeepFake Detection: Current Challenges and Next Steps","date":"2020-03-11","arxiv_id":"2003.09234","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepfakes-for-medical-video-de-identification","title":"Deepfakes for Medical Video De-Identification: Privacy Protection and Diagnostic Information Preservation","date":"2020-02-07","arxiv_id":"2003.00813","repositories_listed":0,"syntology":null},{"url":null,"slug":"fakelocator-robust-localization-of-gan-based","title":"FakeLocator: Robust Localization of GAN-Based Face Manipulations","date":"2020-01-27","arxiv_id":"2001.09598","repositories_listed":0,"syntology":null}],"record_sha256":"0a3aa6d4953d14ffd4caf36d7197f1a28b9ade26ff96b3e6f85a1a1df7f6ad6c","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}