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README

DF40: Toward Next-Generation Deepfake Detection (Project Page; Paper; Download DF40; Checkpoints)

License: CC BY-NC 4.0 Release .10 PyTorch Python

🎉🎉🎉 Our DF40 has been accepted by NeurIPS 2024 D&B track!

Welcome to our work DF40, for next-generation deepfake detection.

In this work, we propose: (1) a diverse deepfake dataset with 40 distinct generations methods; and (2) a comprehensive benchmark for training, evaluation, and analysis.

"Expanding Your Evaluation with 40 distinct High-Quality Fake Data from the FF++ and CDF domains!!"

DF40 Dataset Highlight: The key features of our proposed DF40 dataset are as follows

Forgery Diversity: DF40 comprises 40 distinct deepfake techniques (both representive and SOTA methods are included), facilitating the detection of nowadays' SOTA deepfakes and AIGCs. We provide 10 face-swapping methods, 13 face-reenactment methods, 12 entire face synthesis methods, and 5 face editing.

Forgery Realism: DF40 includes realistic deepfake data created by highly popular generation software and methods, e.g., HeyGen, MidJourney, DeepFaceLab, to simulate real-world deepfakes. We even include the just-released DiT, SiT, PixArt-$\alpha$, etc.

Forgery Scale: DF40 offers million-level deepfake data scale for both images and videos.

Data Alignment: DF40 provides alignment between fake methods and data domains. Most methods (31) are generated under the FF++ and CDF domains. Using our fake data, you can further expand your evaluation (training on FF++ and testing on CDF).

The figure below provides a brief introduction to our DF40 dataset.


The following table displays the statistical description and illustrates the details of our DF40 dataset. Please check our paper for details.


💥 DF40 Dataset

Type ID-Number Generation Method Original Data Source Visual Examples
Face-swapping (FS) 1 FSGAN FF++ and Celeb-DF fsgan-Example
Face-swapping (FS) 2 FaceSwap FF++ and Celeb-DF faceswap-Example
Face-swapping (FS) 3 SimSwap FF++ and Celeb-DF simswap-Example
Face-swapping (FS) 4 InSwapper FF++ and Celeb-DF inswap-Example
Face-swapping (FS) 5 BlendFace FF++ and Celeb-DF blendface-Example
Face-swapping (FS) 6 UniFace FF++ and Celeb-DF uniface-Example
Face-swapping (FS) 7 MobileSwap FF++ and Celeb-DF mobileswap-Example
Face-swapping (FS) 8 e4s FF++ and Celeb-DF e4s-Example
Face-swapping (FS) 9 FaceDancer FF++ and Celeb-DF facedancer-Example
Face-swapping (FS) 10 DeepFaceLab UADFV deepfacelab-Example
Face-reenactment (FR) 11 FOMM FF++ and Celeb-DF fomm-Example
Face-reenactment (FR) 12 FS_vid2vid FF++ and Celeb-DF face_vid2vid-Example
Face-reenactment (FR) 13 Wav2Lip FF++ and Celeb-DF wav2lip-Example
Face-reenactment (FR) 14 MRAA FF++ and Celeb-DF mraa-Example
Face-reenactment (FR) 15 OneShot FF++ and Celeb-DF oneshot-Example
Face-reenactment (FR) 16 PIRender FF++ and Celeb-DF pirender-Example
Face-reenactment (FR) 17 TPSM FF++ and Celeb-DF tpsm-Example
Face-reenactment (FR) 18 LIA FF++ and Celeb-DF lia-Example
Face-reenactment (FR) 19 DaGAN FF++ and Celeb-DF dagan-Example
Face-reenactment (FR) 20 SadTalker FF++ and Celeb-DF sadtalker-Example
Face-reenactment (FR) 21 MCNet FF++ and Celeb-DF mcnet-Example
Face-reenactment (FR) 22 HyperReenact FF++ and Celeb-DF hyperreenact-Example
Face-reenactment (FR) 23 HeyGen FVHQ heygen-Example
Entire Face Synthesis (EFS) 24 VQGAN Finetuning on FF++ and Celeb-DF vqgan-Example
Entire Face Synthesis (EFS) 25 StyleGAN2 Finetuning on FF++ and Celeb-DF stylegan2-Example
Entire Face Synthesis (EFS) 26 StyleGAN3 Finetuning on FF++ and Celeb-DF stylegan3-Example
Entire Face Synthesis (EFS) 27 StyleGAN-XL Finetuning on [FF++](https://github.com/ondy

Core symbols most depended-on inside this repo

load
called by 39
DeepfakeBench_DF40/training/networks/xception_ffd.py
get_block
called by 24
DeepfakeBench_DF40/training/networks/adaface.py
save
called by 23
DeepfakeBench_DF40/training/networks/xception_ffd.py
step
called by 17
DeepfakeBench_DF40/training/optimizor/SAM.py
update
called by 16
DeepfakeBench_DF40/training/metrics/base_metrics_class.py
reset
called by 14
DeepfakeBench_DF40/training/detectors/utils/slowfast/utils/meters.py
parse
called by 13
DeepfakeBench_DF40/training/dataset/utils/SLADD.py
init_weights
called by 12
DeepfakeBench_DF40/training/networks/base_backbone.py

Shape

Method 702
Function 396
Class 200

Languages

Python100%

Modules by API surface

DeepfakeBench_DF40/training/detectors/utils/slowfast/models/video_model_builder.py92 symbols
DeepfakeBench_DF40/training/detectors/utils/slowfast/utils/meters.py51 symbols
DeepfakeBench_DF40/training/detectors/srm_detector.py47 symbols
DeepfakeBench_DF40/training/networks/resnet.py42 symbols
DeepfakeBench_DF40/training/networks/adaface.py42 symbols
DeepfakeBench_DF40/training/networks/time_transformer.py28 symbols
DeepfakeBench_DF40/training/dataset/utils/DeepFakeMask.py26 symbols
DeepfakeBench_DF40/training/networks/xception_ffd.py25 symbols
DeepfakeBench_DF40/training/networks/cls_hrnet.py25 symbols
DeepfakeBench_DF40/training/networks/xception_sladd.py22 symbols
DeepfakeBench_DF40/training/metrics/base_metrics_class.py22 symbols
DeepfakeBench_DF40/training/detectors/recce_detector.py22 symbols

For agents

$ claude mcp add DF40 \
  -- python -m otcore.mcp_server <graph>

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