{"id":2512,"url":"https://github.com/Daisy-Zhang/Awesome-Deepfakes","name":"Awesome-Deepfakes","description":"A list of datasets, tools, papers and code related to Deepfakes.","projects_count":72,"last_synced_at":"2026-10-10T03:00:20.261Z","repository":{"id":38541358,"uuid":"381604592","full_name":"Daisy-Zhang/Awesome-Deepfakes","owner":"Daisy-Zhang","description":"A list of datasets, tools, papers and code related to Deepfakes.","archived":false,"fork":false,"pushed_at":"2021-12-22T12:49:33.000Z","size":19,"stargazers_count":214,"open_issues_count":1,"forks_count":12,"subscribers_count":4,"default_branch":"main","last_synced_at":"2026-09-20T10:10:04.260Z","etag":null,"topics":["awesome","datasets","deepfakes","image","paper-with-code","paperlist","tools","video"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Daisy-Zhang.png","metadata":{},"created_at":"2021-06-30T06:52:53.000Z","updated_at":"2026-09-16T11:02:32.000Z","dependencies_parsed_at":"2022-09-01T00:41:50.103Z","dependency_job_id":null,"html_url":"https://github.com/Daisy-Zhang/Awesome-Deepfakes","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Daisy-Zhang/Awesome-Deepfakes","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Daisy-Zhang%2FAwesome-Deepfakes","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Daisy-Zhang%2FAwesome-Deepfakes/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Daisy-Zhang%2FAwesome-Deepfakes/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Daisy-Zhang%2FAwesome-Deepfakes/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Daisy-Zhang","download_url":"https://codeload.github.com/Daisy-Zhang/Awesome-Deepfakes/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Daisy-Zhang%2FAwesome-Deepfakes/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":343680568,"owners_count":38152326,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-10-03T21:59:58.778Z","status":"online","status_checked_at":"2026-10-10T02:00:07.419Z","response_time":65,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"created_at":"2024-01-04T20:13:09.472Z","updated_at":"2026-10-10T03:00:20.261Z","primary_language":null,"list_of_lists":false,"displayable":true,"categories":["Papers","Tools","Datasets"],"sub_categories":["CVPR","ICLR","Image Datasets","Video Datasets","ICCV","ECCV","IJCAI","AAAI","ACM MM","TPAMI"],"readme":"# Awesome Deepfakes![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)\n\nA list of Deepfakes datasets, tools, papers and code. If this list help you in your research, a star is my pleasure.\n\nIf you want to contribute to this list, welcome to send me a pull request or contact me :) .\n\nThis repo only collect papers related to Deepfake Generation. If you are also interested in Deepfake Detection, please refer to: [Awesome Deepfakes Detection](https://github.com/Daisy-Zhang/awesome-deepfakes-detection).\n\n\n\n## Table of Contents\n\n* [Datasets](#datasets)\n  * [Video Datasets](#video-datasets)\n  * [Image Datasets](#image-datasets)\n* [Tools](#tools)\n* [Papers](#papers)\n  * [CVPR](#cvpr)\n  * [ICCV](#iccv)\n  * [ECCV](#eccv)\n  * [ICLR](#iclr)\n  * [IJCAI](#ijcai)\n  * [AAAI](#aaai)\n  * [ACM MM](#acm-mm)\n  * [TPAMI](#tpami)\n\n\n\n## Datasets\n\n### Video Datasets\n\n* **UADFV**: \"Exposing Deep Fakes Using Inconsistent Head Poses.\" [Paper](https://arxiv.org/abs/1811.00661)\n* **EBV**: \"In Ictu Oculi: Exposing AI Generated Fake Face Videos by Detecting Eye Blinking.\" [Paper](https://arxiv.org/abs/1806.02877)    [Download](http://www.cs.albany.edu/~lsw/downloads.html)\n* **Deepfake-TIMIT**: \"DeepFakes: a New Threat to Face Recognition? Assessment and Detection.\" [Paper](https://arxiv.org/abs/1812.08685)    [Download](https://conradsanderson.id.au/vidtimit/)\n* **DFFD**: \"DFFD: Diverse Fake Face Dataset.\" [Paper](http://cvlab.cse.msu.edu/dffd-diverse-fake-face-dataset.html)    [Download](http://cvlab.cse.msu.edu/dffd-dataset.html)\n* **Wild Deepfake**: \"WildDeepfake: A Challenging Real-World Dataset for Deepfake Detection.\" [Paper](https://arxiv.org/abs/2101.01456)    [Download](https://github.com/deepfakeinthewild/deepfake-in-the-wild)\n* **Celeb-DF (v1)**: \"Celeb-DF: A Large-scale Challenging Dataset for DeepFake Forensics.\" [Paper](https://openaccess.thecvf.com/content_CVPR_2020/papers/Li_Celeb-DF_A_Large-Scale_Challenging_Dataset_for_DeepFake_Forensics_CVPR_2020_paper.pdf)    [Download](https://github.com/yuezunli/celeb-deepfakeforensics/tree/master/Celeb-DF-v1)\n* **Celeb-DF (v2)**: \"Celeb-DF: A Large-scale Challenging Dataset for DeepFake Forensics.\" [Paper](https://openaccess.thecvf.com/content_CVPR_2020/papers/Li_Celeb-DF_A_Large-Scale_Challenging_Dataset_for_DeepFake_Forensics_CVPR_2020_paper.pdf)    [Download](https://github.com/yuezunli/celeb-deepfakeforensics/tree/master/Celeb-DF-v2)\n* **DFDC**: \"The DeepFake Detection Challenge (DFDC) Dataset.\" [Paper](https://arxiv.org/abs/2006.07397)    [Download](https://www.kaggle.com/c/deepfake-detection-challenge/data) \n* **Deeper Forensic**: \"DeeperForensics-1.0: A Large-Scale Dataset for Real-World Face Forgery Detection.\" [Paper](https://openaccess.thecvf.com/content_CVPR_2020/papers/Jiang_DeeperForensics-1.0_A_Large-Scale_Dataset_for_Real-World_Face_Forgery_Detection_CVPR_2020_paper.pdf)    [Download](https://github.com/EndlessSora/DeeperForensics-1.0)\n* **FaceForensic++**: \"FaceForensics++: Learning to Detect Manipulated Facial Images.\" [Paper](https://arxiv.org/abs/1901.08971)    [Download](https://github.com/ondyari/FaceForensics)\n* **DFGC**: \"DFGC 2021: A DeepFake Game Competition.\" [Paper](https://arxiv.org/abs/2106.01217)    [Dowload](https://github.com/bomb2peng/DFGC_starterkit)\n* **FFIW-10K**: \"Face Forensics in the Wild.\" [Paper](https://arxiv.org/abs/2103.16076)    [Download](https://github.com/tfzhou/FFIW)\n* **ForgeryNet**: \"ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysis.\" [Paper](https://arxiv.org/abs/2103.05630)    [Download](https://github.com/yinanhe/forgerynet)\n\n|                     | Real Videos | Fake Videos |\n| :-----------------: | :---------: | :---------: |\n|        UADFV        |     49      |     49      |\n|   Deepfake-TIMIT    |     320     |     640     |\n|        DFFD         |    1000     |    3000     |\n|    Celeb-DF (v2)    |     590     |    5639     |\n|        DFDC         |   23,564    |   104,500   |\n| DeeperForensics-1.0 |   50,000    |   10,000    |\n|   FaceForensic++    |    1000     |    5000     |\n|     ForgeryNet      |   99,630    |   121,617   |\n\n\n\n### Image Datasets\n\n* **DFFD**: \"On the Detection of Digital Face Manipulation.\" [Paper](https://openaccess.thecvf.com/content_CVPR_2020/papers/Dang_On_the_Detection_of_Digital_Face_Manipulation_CVPR_2020_paper.pdf)    [Download](http://cvlab.cse.msu.edu/project-ffd.html)\n* **FFHQ**: \"A Style-Based Generator Architecture for Generative Adversarial Networks.\" [Paper](https://openaccess.thecvf.com/content_CVPR_2019/papers/Karras_A_Style-Based_Generator_Architecture_for_Generative_Adversarial_Networks_CVPR_2019_paper.pdf)    [Download](https://github.com/NVlabs/ffhq-dataset)\n* **iFakeFaceDB**: \"GANprintR: Improved Fakes and Evaluation of the State of the Art in Face Manipulation Detection.\" [Paper](https://arxiv.org/abs/1911.05351)    [Download](https://github.com/socialabubi/iFakeFaceDB)\n* **100k Faces Generated by AI (Online)**: [Download](https://generated.photos/datasets)\n\n|             | Real Images |    Fake Images     |\n| :---------: | :---------: | :----------------: |\n|    DFFD     |   58,703    |      240,336       |\n|    FFHQ     |      -      | 70,000 (GAN-based) |\n| iFakeFaceDB |      -      | 87,000 (StyleGAN)  |\n| 100k Faces  |      -      | 100,000 (StyleGAN) |\n| ForgeryNet  |  1,438,201  |     1,457,861      |\n\n\n\n## Tools\n\n* **Deepfakes-FaceSwap**: [Github](https://github.com/deepfakes/faceswap)\n* **FaceSwap**: [Github](https://github.com/MarekKowalski/FaceSwap/)\n* **dfaker**: [Github](https://github.com/dfaker/df)\n* **FaceSwap-GAN**: [Github](https://github.com/shaoanlu/faceswap-GAN)\n* **Face2Face**: [Github](https://github.com/datitran/face2face-demo)\n* **DeepFaceLab**: [Github](https://github.com/iperov/DeepFaceLab)\n* **DeepFaceLive**: [Github](https://github.com/iperov/DeepFaceLive)\n* **FaceSwap Online**: [Website](https://faceswap.dev/)\n* **MyVoiceYourFace**: [Website](https://myvoiceyourface.com/)\n* **Online Deepfake Maker**: [Website](https://deepfakesweb.com/)\n* **Online Deepfake Video Creator**: [Website](https://mmasked.com/)\n* **Generated Photos**: [Website](https://generated.photos/)\n\n\n\n## Papers\n\n### CVPR\n\n* \"TediGAN: Text-Guided Diverse Face Image Generation and Manipulation\", CVPR 2021: [Paper](https://arxiv.org/pdf/2012.03308v2.pdf)    [Github](https://github.com/IIGROUP/TediGAN)\n* \"One Shot Face Swapping on Megapixels\", CVPR 2021: [Paper](https://arxiv.org/pdf/2105.04932v1.pdf)    [Github](https://github.com/zyainfal/One-Shot-Face-Swapping-on-Megapixels)\n* \"Face Forensics in the Wild\", CVPR 2021: [Paper](https://arxiv.org/abs/2103.16076)    [Github](https://github.com/tfzhou/FFIW)\n* \"High-Fidelity and Arbitrary Face Editing\", CVPR 2021: [Paper](https://arxiv.org/abs/2103.15814)\n\n* \"Celeb-DF: A Large-Scale Challenging Dataset for DeepFake Forensics\", CVPR 2020: [Paper](https://openaccess.thecvf.com/content_CVPR_2020/html/Li_Celeb-DF_A_Large-Scale_Challenging_Dataset_for_DeepFake_Forensics_CVPR_2020_paper.html)    [Github](https://github.com/yuezunli/celeb-deepfakeforensics)\n* \"DeeperForensics-1.0: A Large-Scale Dataset for Real-World Face Forgery Detection\", CVPR 2020: [Paper](https://openaccess.thecvf.com/content_CVPR_2020/html/Jiang_DeeperForensics-1.0_A_Large-Scale_Dataset_for_Real-World_Face_Forgery_Detection_CVPR_2020_paper.html)       [Github](https://github.com/EndlessSora/DeeperForensics-1.0)\n* \"MaskGAN: Towards Diverse and Interactive Facial Image Manipulation\", CVPR 2020: [Paper](https://ieeexplore.ieee.org/document/9157722/)    [Github](https://github.com/switchablenorms/CelebAMask-HQ)\n* \"Semantic Component Decomposition for Face Attribute Manipulation\", CVPR 2019: [Paper](https://openaccess.thecvf.com/content_CVPR_2019/papers/Chen_Semantic_Component_Decomposition_for_Face_Attribute_Manipulation_CVPR_2019_paper.pdf)\n* \"A Style-Based Generator Architecture for Generative Adversarial Networks\", CVPR 2019: [Paper](https://arxiv.org/abs/1812.04948)\n* \"StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation\",CVPR 2018: [Paper](https://openaccess.thecvf.com/content_cvpr_2018/papers/Choi_StarGAN_Unified_Generative_CVPR_2018_paper.pdf)\n\n### ICCV\n\n* \"A Latent Transformer for Disentangled Face Editing in Images and Videos\", ICCV 2021: [Paper](https://arxiv.org/abs/2106.11895) [Github](https://github.com/InterDigitalInc/Latent-Transformer)\n* \"Diagonal Attention and Style-based GAN for Content-Style Disentanglement in\n  Image Generation and Translation\", ICCV 2021: [Paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Kwon_Diagonal_Attention_and_Style-Based_GAN_for_Content-Style_Disentanglement_in_Image_ICCV_2021_paper.pdf)\n* \"Dual Projection Generative Adversarial Networks for Conditional Image\n  Generation\", ICCV 2021: [Paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Han_Dual_Projection_Generative_Adversarial_Networks_for_Conditional_Image_Generation_ICCV_2021_paper.pdf)\n* \"LoFGAN: Fusing Local Representations for Few-shot Image Generation\", ICCV 2021: [Paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Gu_LoFGAN_Fusing_Local_Representations_for_Few-Shot_Image_Generation_ICCV_2021_paper.pdf) [Github](https://github.com/edward3862/LoFGAN-pytorch)\n* \"Semi-Supervised Single-Stage Controllable GANs for Conditional Fine-Grained\n  Image Generation\": [Paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Chen_Semi-Supervised_Single-Stage_Controllable_GANs_for_Conditional_Fine-Grained_Image_Generation_ICCV_2021_paper.pdf)\n* \"Unsupervised Image Generation with Infinite Generative Adversarial Networks\", ICCV 2021: [Paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Ying_Unsupervised_Image_Generation_With_Infinite_Generative_Adversarial_Networks_ICCV_2021_paper.pdf) [Github](https://github.com/yinghdb/MICGANs)\n\n* \"Make a Face: Towards Arbitrary High Fidelity Face Manipulation\", ICCV 2019: [Paper](https://openaccess.thecvf.com/content_ICCV_2019/papers/Qian_Make_a_Face_Towards_Arbitrary_High_Fidelity_Face_Manipulation_ICCV_2019_paper.pdf)\n* \"FSGAN: Subject Agnostic Face Swapping and Reenactment\", ICCV 2019: [Paper](https://openaccess.thecvf.com/content_ICCV_2019/papers/Nirkin_FSGAN_Subject_Agnostic_Face_Swapping_and_Reenactment_ICCV_2019_paper.pdf)    [Github](https://github.com/YuvalNirkin/fsgan)\n* \"SC-FEGAN: Face Editing Generative Adversarial Network with User’s Sketch and Color\", ICCV 2019: [Paper](https://openaccess.thecvf.com/content_ICCV_2019/papers/Jo_SC-FEGAN_Face_Editing_Generative_Adversarial_Network_With_Users_Sketch_and_ICCV_2019_paper.pdf)    [Github](https://github.com/run-youngjoo/SC-FEGAN)\n\n### ECCV\n\n* \"Hierarchical Face Aging through Disentangled Latent Characteristics\", ECCV 2020: [Paper](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123480086.pdf)\n* \"CONFIG: Controllable Neural Face Image Generation\", ECCV 2020: [Paper](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123560290.pdf)\n* \"CAFE-GAN: Arbitrary Face Attribute Editing with Complementary Attention Feature\", ECCV 2020: [paper](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123590511.pdf)\n* \"High Resolution Zero-Shot Domain Adaptation of Synthetically Rendered Face Images\", ECCV 2020: [Paper](http://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123730222.pdf)\n\n* \"Attribute-Guided Face Generation Using Conditional CycleGAN\",ECCV 2018: [Paper](http://www.ecva.net/papers/eccv_2018/papers_ECCV/papers/Yongyi_Lu_Attribute-Guided_Face_Generation_ECCV_2018_paper.pdf)\n* \"X2Face: A network for controlling face generation using images, audio, and pose codes\", ECCV 2018: [Paper](http://www.ecva.net/papers/eccv_2018/papers_ECCV/papers/Olivia_Wiles_X2Face_A_network_ECCV_2018_paper.pdf)\n* \"Generative Adversarial Network with Spatial Attention for Face Attribute Editing\", ECCV 2018: [Paper](http://www.ecva.net/papers/eccv_2018/papers_ECCV/papers/Gang_Zhang_Generative_Adversarial_Network_ECCV_2018_paper.pdf)\n* \"Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model\", ECCV 2018: [Paper](http://www.ecva.net/papers/eccv_2018/papers_ECCV/papers/Baris_Gecer_Semi-supervised_Adversarial_Learning_ECCV_2018_paper.pdf)    [Github](https://github.com/barisgecer/facegan)\n* \"ELEGANT: Exchanging Latent Encodings with GAN for Transferring Multiple Face Attributes\", ECCV 2018: [Paper](http://www.ecva.net/papers/eccv_2018/papers_ECCV/papers/Taihong_Xiao_ELEGANT_Exchanging_Latent_ECCV_2018_paper.pdf)    [Github](https://github.com/Prinsphield/ELEGANT)\n* \"A Hybrid Model for Identity Obfuscation by Face Replacement\", ECCV 2018: [Paper](http://www.ecva.net/papers/eccv_2018/papers_ECCV/papers/Qianru_Sun_A_Hybrid_Model_ECCV_2018_paper.pdf)\n\n### ICLR\n\n* \"CCGAN: CONTINUOUS CONDITIONAL GENERATIVE ADVERSARIAL NETWORKS FOR IMAGE GENERATION\", ICLR 2021: [Paper](https://openreview.net/pdf?id=PrzjugOsDeE)    [Github](https://github.com/UBCDingXin/improved_CcGAN)\n* \"FROM INFERENCE TO GENERATION: END-TO-END FULLY SELF-SUPERVISED GENERATION OF HUMAN FACE FROM SPEECH\", ICLR 2020: [Paper](https://openreview.net/pdf?id=H1guaREYPr)\n* \"Progressive Growing of GANs for Improved Quality, Stability, and Variation\", ICLR 2018: [Paper](https://arxiv.org/abs/1710.10196)    [Github](https://github.com/tkarras/progressive_growing_of_gans)\n\n### IJCAI\n\n* \"Reference-guided Face Component Editing\", IJCAI 2020: [Paper](https://arxiv.org/abs/2006.02051)\n* \"Talking Face Generation by Conditional Recurrent Adversarial Network\", IJCAI 2019: [Paper](https://www.ijcai.org/Proceedings/2019/0129.pdf)    [Github](https://github.com/susanqq/Talking_Face_Generation)\n\n### AAAI\n\n* \"GDFace: Gated Deformation for Multi-view Face Image Synthesis\", AAAI 2020: [Paper](http://www.shengfenghe.com/qfy-content/uploads/2020/04/4aa081262dd1fafd6ffb9b95444dc39b.pdf)\n* \"CG-GAN: An Interactive Evolutionary GAN-based Approach for Facial Composite Generation\", AAAI 2020: [Paper](https://pure.itu.dk/portal/files/85687312/1912.05020.pdf)\n\n### ACM MM\n\n* \"DeepFacePencil: Creating Face Images from Freehand Sketches\", ACM MM 2020: [Paper](https://dl.acm.org/doi/10.1145/3394171.3413684)\n* \"Talking Face Generation with Expression-Tailored Generative Adversarial Network\", ACM MM 2020: [Paper](https://dl.acm.org/doi/10.1145/3394171.3413844)\n* \"SimSwap: An Efficient Framework For High Fidelity Face Swapping\", ACM MM 2020: [Paper](https://dl.acm.org/doi/10.1145/3394171.3413630)\n* \"FakePolisher: Making DeepFakes More Detection-Evasive by Shallow Reconstruction\", ACM MM 2020: [Paper](https://dl.acm.org/doi/10.1145/3394171.3413732)\n* \"Towards Automatic Face-to-Face Translation\", ACM MM 2019: [Paper](https://arxiv.org/abs/2003.00418v1)    [Github](https://github.com/Rudrabha/LipGAN)\n* \"LinesToFacePhoto: Face Photo Generation From Lines With Conditional Self-Attention Generative Adversarial Networks\", ACM MM 2019: [Paper](https://dl.acm.org/doi/10.1145/3343031.3350854)\n\n### TPAMI\n\n* \"InterFaceGAN: Interpreting the Disentangled Face Representation Learned by GANs\", TPAMI 2020: [Paper](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=\u0026arnumber=9241434)\n","projects_url":"https://awesome.ecosyste.ms/api/v1/lists/daisy-zhang%2Fawesome-deepfakes/projects"}