Papers with Code 아카이브
3D Shape Reconstruction from Videos
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/zyainfal/One-Shot-Face-Swapping-on-Megapixels
공식 코드https://github.com/AlgoHunt/Face-Xray
https://github.com/AshikaAnand12/FaceManipulation
DeepFakes and Beyond: A Survey of Face Manipulation and Fake Detection
https://github.com/Baukebrenninkmeijer/HackGAN
FaceForensics++: Learning to Detect Manipulated Facial Images
https://github.com/BiDAlab/DeepFakesON-Phys
DeepFakesON-Phys: DeepFakes Detection based on Heart Rate Estimation
https://github.com/CatoGit/Comparing-the-Performance-of-Deepfake-Detection-Methods-on-Benchmark-Datasets
Celeb-DF: A Large-scale Challenging Dataset for DeepFake Forensics
https://github.com/Daisy-Zhang/Face-X-ray
https://github.com/DataScienceNigeria/Fake-Detection-dataset-for-deepfake-from-Google-and-Jigsaw
FaceForensics++: Learning to Detect Manipulated Facial Images
https://github.com/FaceOnLive/DeepFake-Detection-SDK-Linux
https://github.com/HongguLiu/MesoNet.Pytorch
https://github.com/MS-Mind/MS-Code-02/tree/main/configs/convnext
https://github.com/MalayAgarwal-Lee/MesoNet-DeepFakeDetection
https://github.com/Manasi2001/Spoofed-Speech-Attribution
AASIST: Audio Anti-Spoofing using Integrated Spectro-Temporal Graph Attention Networks
https://github.com/ManyiLee/Open-world-Deepfake-Detection-Network
ODDN: Addressing Unpaired Data Challenges in Open-World Deepfake Detection on Online Social Networks
https://github.com/MindCode-4/code-5/tree/main/wavlm
https://github.com/MindSpore-paper-code-3/code2/tree/main/convnext
https://github.com/QiShanZhang/SLSforASVspoof-2021-DF
https://github.com/Raj-08/Deepfake-Detection-Mesonet
https://github.com/Ramneantu/deepfake-detection
https://github.com/Recognito-Vision/Face-SDK-Linux-Demos
Unmasking Deepfake Faces from Videos Using An Explainable Cost-Sensitive Deep Learning Approach
https://github.com/Recognito-Vision/Linux-FaceRecognition-FaceLivenessDetection
https://github.com/SuyashSonawane/fakedetector
FaceForensics++: Learning to Detect Manipulated Facial Images
https://github.com/YvanG/VQGAN-CLIP
https://github.com/aiiu-lab/dfd-fcg
https://github.com/aimagelab/elsa_coco-fake
Parents and Children: Distinguishing Multimodal DeepFakes from Natural Images
https://github.com/alibaba/EasyNLP/tree/master/examples/text2image_generation
https://github.com/ammarahhashmi/Multimodal-Forgery-Detection-Using-Ensemble-Learning
https://github.com/audio-df-ucb/clonedvoicedetection
https://github.com/avishai111/One-Class-Learning-with-Adaptive-Centroid-Shift-for-Audio-Deepfake-Detection
One-Class Learning with Adaptive Centroid Shift for Audio Deepfake Detection
https://github.com/beibuwandeluori/DFGC_Detection
Celeb-DF: A Large-scale Challenging Dataset for DeepFake Forensics
https://github.com/bigaandsmallq/d3
D$^3$: Scaling Up Deepfake Detection by Learning from Discrepancy
https://github.com/cc-hpc-itwm/UpConv
https://github.com/cecile-hi/regularized-adaptive-weight-modification
What to Remember: Self-Adaptive Continual Learning for Audio Deepfake Detection
https://github.com/deepfakes/faceswap
DeepFakes and Beyond: A Survey of Face Manipulation and Fake Detection
https://github.com/dome272/VQGAN
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.