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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/svddchallenge/ctrsvdd2024_baseline
공식 코드SVDD Challenge 2024: A Singing Voice Deepfake Detection Challenge Evaluation Plan
https://github.com/swagshaw/xlsr-mamba
공식 코드XLSR-Mamba: A Dual-Column Bidirectional State Space Model for Spoofing Attack Detection
https://github.com/taco-group/hfmf
공식 코드HFMF: Hierarchical Fusion Meets Multi-Stream Models for Deepfake Detection
https://github.com/talkingnow/HM-Conformer
공식 코드https://github.com/talreiss/factor
공식 코드https://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 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.