Papers with Code 아카이브
DeepFake Detection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 5
- 평가표
- 11
- 보존된 평가 기록
- 30
DeepFake Detection is the task of detecting fake videos or images that have been generated using deep learning techniques. Deepfakes are created by using machine learning algorithms to manipulate or replace parts of an original video or image, such as the face of a person. The goal of deepfake detection is to identify such manipulations and distinguish them from real videos or images.
Description source: DeepFakes: a New Threat to Face Recognition? Assessment and Detection
Image source: DeepFakes: a New Threat to Face Recognition? Assessment and Detection
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/tamlhp/dfd_benchmark
공식 코드A War Beyond Deepfake: Benchmarking Facial Counterfeits and Countermeasures
https://github.com/tizfa/tweepfake_deepfake_text_detection
공식 코드https://github.com/tobuta/PolyGlotFake
공식 코드PolyGlotFake: A Novel Multilingual and Multimodal DeepFake Dataset
https://github.com/vcbsl/audio-visual-deepfake
공식 코드Contextual Cross-Modal Attention for Audio-Visual Deepfake Detection and Localization
https://github.com/vishal3477/Reverse_Engineering_GMs
공식 코드Reverse Engineering of Generative Models: Inferring Model Hyperparameters from Generated Images
https://github.com/vladhondru25/exddv
공식 코드ExDDV: A New Dataset for Explainable Deepfake Detection in Video
https://github.com/vpsg-research/waveguard
공식 코드https://github.com/wangjk666/M2TR-Multi-modal-Multi-scale-Transformers-for-Deepfake-Detection
공식 코드M2TR: Multi-modal Multi-scale Transformers for Deepfake Detection
https://github.com/wangty1/DCPT
공식 코드Deep Convolutional Pooling Transformer for Deepfake Detection
https://github.com/wangty1/LampMark
공식 코드LampMark: Proactive Deepfake Detection via Training-Free Landmark Perceptual Watermarks
https://github.com/wasim004/FAME
공식 코드FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes
https://github.com/wolo-wolo/FFR_FD-Effective-and-Fast-Detection-of-DeepFakes-Based-on-Feature-Point-Defects
공식 코드FFR_FD: Effective and Fast Detection of DeepFakes Based on Feature Point Defects
https://github.com/wolo-wolo/FSFM
공식 코드https://github.com/xianyunsun/vra
공식 코드https://github.com/xieyuankun/Codecfake
공식 코드The Codecfake Dataset and Countermeasures for the Universally Detection of Deepfake Audio
https://github.com/xieyuankun/all-type-add
공식 코드Detect All-Type Deepfake Audio: Wavelet Prompt Tuning for Enhanced Auditory Perception
https://github.com/xieyuankun/alm-add
공식 코드Does Current Deepfake Audio Detection Model Effectively Detect ALM-based Deepfake Audio?
https://github.com/xieyuankun/fsd-dataset
공식 코드https://github.com/xieyuankun/st-codecfake
공식 코드Neural Codec Source Tracing: Toward Comprehensive Attribution in Open-Set Condition
https://github.com/xjchengit/singgraph
공식 코드https://github.com/xuyingzhongguo/deepfakeannotations
공식 코드Analyzing Fairness in Deepfake Detection With Massively Annotated Databases
https://github.com/xuyingzhongguo/mcx-api
공식 코드Learning Pairwise Interaction for Generalizable DeepFake Detection
https://github.com/xuyingzhongguo/vod
공식 코드VoD: Learning Volume of Differences for Video-Based Deepfake Detection
https://github.com/yaselley/ssl_layerwise_deepfake
공식 코드Comprehensive Layer-wise Analysis of SSL Models for Audio Deepfake Detection
https://github.com/yermandy/deepfake-detection
공식 코드Unlocking the Hidden Potential of CLIP in Generalizable Deepfake Detection
https://github.com/yoctta/multiple-attention
공식 코드https://github.com/yongyizang/SingFake
공식 코드https://github.com/yunyikristy/global_local
공식 코드https://github.com/yzyouzhang/asvspoof2021_air
공식 코드UR Channel-Robust Synthetic Speech Detection System for ASVspoof 2021
https://github.com/zhenglab/ffdbackbone
공식 코드https://github.com/zhu00121/universal-representation-dynamics-of-deepfake-speech
공식 코드https://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
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.