Papers with Code 아카이브
3D Shape Reconstruction from Videos
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/flynn-chen/faceforensics_benchmark
FaceForensics++: Learning to Detect Manipulated Facial Images
https://github.com/gewanying/shap-anti-spoofing
https://github.com/ghua-ac/end-to-end-synthetic-speech-detection
https://github.com/horizontel/aigibench
Generalizable Deepfake Detection via Effective Local-Global Feature Extraction
https://github.com/hyhchaos/FakePolisher
FakePolisher: Making DeepFakes More Detection-Evasive by Shallow Reconstruction
https://github.com/hyn2028/llm-cxr
https://github.com/hzlsaber/sida
https://github.com/jhchang/DFDC
FaceForensics++: Learning to Detect Manipulated Facial Images
https://github.com/jmpu/deepfaketextdetection
https://github.com/joanrod/ocr-vqgan
https://github.com/joh-fischer/PlantLDM
https://github.com/josebeo2016/BTS-Encoder-ASVspoof
https://github.com/jtchen0528/PCL-I2G
https://github.com/kprav3/DeepFakeDetection_DIP
https://github.com/lixucuhk/ASV-anti-spoofing-with-Res2Net
Replay and Synthetic Speech Detection with Res2net Architecture
https://github.com/lixucuhk/Channel-wise-Gated-Res2Net
Replay and Synthetic Speech Detection with Res2net Architecture
https://github.com/maragori/DeepfakeForensics-v1
https://github.com/neverUseThisName/Face-X-Ray
https://github.com/nicksunday/deepfake-music-detector
https://github.com/paarthneekhara/adversarialdeepfakes
Adversarial Deepfakes: Evaluating Vulnerability of Deepfake Detectors to Adversarial Examples
https://github.com/piotrkawa/audio-deepfake-source-tracing
https://github.com/pothabattulasantosh/Detection-of-face-Manipulated-videos
FaceForensics++: Learning to Detect Manipulated Facial Images
https://github.com/pothabattulasantosh/Detection-of-facial-Manipulated-videos
FaceForensics++: Learning to Detect Manipulated Facial Images
https://github.com/purdue-m2/robust_fairness_withNoisy_labels
Analyzing Fairness in Deepfake Detection With Massively Annotated Databases
https://github.com/pwc-1/Paper-9/tree/main/5/wavlm
https://github.com/qishanzhang/slsforadd
https://github.com/sahibzadaadil/Lip-Sync-Matters-A-Novel-Multimodal-Forgery-Detector
https://github.com/samb-t/unleashing-transformers
https://github.com/seongilp/DFE604-2020F-FinalProject
FaceForensics++: Learning to Detect Manipulated Facial Images
https://github.com/smu-ivpl/DeepfakeDetection
https://github.com/takhemlata/ssl_anti-spoofing
https://github.com/tgisaturday/taming-transformers-tpu
https://github.com/twyunting/Deepfake_Video_Classifier
FaceForensics++: Learning to Detect Manipulated Facial Images
https://github.com/v-iashin/SpecVQGAN
https://github.com/wangjk666/PyDeepFakeDet
M2TR: Multi-modal Multi-scale Transformers for Deepfake Detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.