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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/amforever/fmfcc-a
공식 코드FMFCC-A: A Challenging Mandarin Dataset for Synthetic Speech Detection
https://github.com/andrekassis/ai-watermark
공식 코드UnMarker: A Universal Attack on Defensive Image Watermarking
https://github.com/anmol2059/svdd2024
공식 코드https://github.com/anonrep/iba-for-video-sequences
공식 코드Extending Information Bottleneck Attribution to Video Sequences
https://github.com/anonymoususera/ava
공식 코드AVA: Inconspicuous Attribute Variation-based Adversarial Attack bypassing DeepFake Detection
https://github.com/anubhav1997/youneednodataset
공식 코드A Dataless FaceSwap Detection Approach Using Synthetic Images
https://github.com/awsaf49/sonics
공식 코드https://github.com/bit-ml/DeCLIP
공식 코드DeCLIP: Decoding CLIP representations for deepfake localization
https://github.com/bit-ml/avh-align
공식 코드Circumventing shortcuts in audio-visual deepfake detection datasets with unsupervised learning
https://github.com/bit-ml/dolos
공식 코드Weakly-supervised deepfake localization in diffusion-generated images
https://github.com/bok-bok/MSOC
공식 코드A Multi-Stream Fusion Approach with One-Class Learning for Audio-Visual Deepfake Detection
https://github.com/boutiquelee/deepfakeempiricalstudy
공식 코드How Generalizable are Deepfake Image Detectors? An Empirical Study
https://github.com/cc-hpc-itwm/DeepFakeDetection
공식 코드https://github.com/cfeng16/audio-visual-forensics
공식 코드Self-Supervised Video Forensics by Audio-Visual Anomaly Detection
https://github.com/chandlerbing65nm/FakeImageDetection
공식 코드https://github.com/chelsea234/hifi_ifdl
공식 코드DeepFake-O-Meter v2.0: An Open Platform for DeepFake Detection
https://github.com/chelsea234/m2f2_det
공식 코드Rethinking Vision-Language Model in Face Forensics: Multi-Modal Interpretable Forged Face Detector
https://github.com/chenhaoxing/DeMamba
공식 코드DeMamba: AI-Generated Video Detection on Million-Scale GenVideo Benchmark
https://github.com/chuangchuangtan/c2p-clip-deepfakedetection
공식 코드C2P-CLIP: Injecting Category Common Prompt in CLIP to Enhance Generalization in Deepfake Detection
https://github.com/chuangchuangtan/data-independent-operator
공식 코드https://github.com/chuangchuangtan/freqnet-deepfakedetection
공식 코드Frequency-Aware Deepfake Detection: Improving Generalizability through Frequency Space Learning
https://github.com/chuangchuangtan/npr-deepfakedetection
공식 코드https://github.com/clad23/clad
공식 코드CLAD: Robust Audio Deepfake Detection Against Manipulation Attacks with Contrastive Learning
https://github.com/clovaai/aasist
공식 코드AASIST: Audio Anti-Spoofing using Integrated Spectro-Temporal Graph Attention Networks
https://github.com/clpeng/Awesome-Face-Forgery-Generation-and-Detection
공식 코드Countering Malicious DeepFakes: Survey, Battleground, and Horizon
https://github.com/controlnet/av-deepfake1m
공식 코드AV-Deepfake1M: A Large-Scale LLM-Driven Audio-Visual Deepfake Dataset
https://github.com/croitorualin/biodeep
공식 코드Deepfake Media Generation and Detection in the Generative AI Era: A Survey and Outlook
https://github.com/cure-lab/DeciWatch
공식 코드DeciWatch: A Simple Baseline for 10x Efficient 2D and 3D Pose Estimation
https://github.com/cyjie429/rego
공식 코드Region-Based Optimization in Continual Learning for Audio Deepfake Detection
https://github.com/dan8991/the-sound-of-silence
공식 코드The Sound of Silence: Efficiency of First Digit Features in Synthetic Audio Detection
https://github.com/danmohaha/celeb-deepfakeforensics
공식 코드Celeb-DF: A Large-scale Challenging Dataset for DeepFake Forensics
https://github.com/dash-lab/fakeavceleb
공식 코드FakeAVCeleb: A Novel Audio-Video Multimodal Deepfake Dataset
https://github.com/davidcombei/ai4t
공식 코드Unmasking real-world audio deepfakes: A data-centric approach
https://github.com/davide-coccomini/Combining-EfficientNet-and-Vision-Transformers-for-Video-Deepfake-Detection
공식 코드Combining EfficientNet and Vision Transformers for Video Deepfake Detection
https://github.com/davide-coccomini/Combining-EfficientNet-and-Vision-Transformersfor-Video-Deepfake-Detection
공식 코드Combining EfficientNet and Vision Transformers for Video Deepfake Detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.