https://github.com/xuyingzhongguo/deepfakeannotations
공식 코드Analyzing Fairness in Deepfake Detection With Massively Annotated Databases
Papers with Code 아카이브
3D Face Reconstruction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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3D Face Reconstruction is a computer vision task that involves creating a 3D model of a human face from a 2D image or a set of images. The goal of 3D face reconstruction is to reconstruct a digital 3D representation of a person's face, which can be used for various applications such as animation, virtual reality, and biometric identification.
<span style="color:grey; opacity: 0.6">( Image credit: 3DDFA_V2 )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
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/xxtars/emo-llama
공식 코드EMO-LLaMA: Enhancing Facial Emotion Understanding with Instruction Tuning
https://github.com/ya332/robust_sleepnets
공식 코드https://github.com/yafuly/deepfaketextdetect
공식 코드https://github.com/yafuly/mage
공식 코드https://github.com/yaoing/dan
공식 코드Distract Your Attention: Multi-head Cross Attention Network for Facial Expression Recognition
https://github.com/yaojieliu/CVPR2019-DeepTreeLearningForZeroShotFaceAntispoofing
공식 코드https://github.com/yaojieliu/ECCV20-STDN
공식 코드https://github.com/yaojieliu/ECCV2018-FaceDeSpoofing
공식 코드https://github.com/yaojieliu/ICCVW2017-DenseFaceAlignment
공식 코드https://github.com/yaselley/ssl_layerwise_deepfake
공식 코드Comprehensive Layer-wise Analysis of SSL Models for Audio Deepfake Detection
https://github.com/ydc123/Dark_Surrogate_Model
공식 코드Boosting the Adversarial Transferability of Surrogate Models with Dark Knowledge
https://github.com/ydwen/opensphere/blob/main/opensphere/module/head/simple.py
공식 코드https://github.com/yelboudouri/EmoNeXt
공식 코드https://github.com/yerfor/Real3DPortrait
공식 코드Real3D-Portrait: One-shot Realistic 3D Talking Portrait Synthesis
https://github.com/yermandy/deepfake-detection
공식 코드Unlocking the Hidden Potential of CLIP in Generalizable Deepfake Detection
https://github.com/ygtxr1997/reliableswap
공식 코드ReliableSwap: Boosting General Face Swapping Via Reliable Supervision
https://github.com/yingjiacheng/restorerid
공식 코드RestorerID: Towards Tuning-Free Face Restoration with ID Preservation
https://github.com/yinhefeng/LCLRRDL
공식 코드Face Recognition via Locality Constrained Low Rank Representation and Dictionary Learning
https://github.com/yinhefeng/soigo
공식 코드Face recognition via compact second order image gradient orientations
https://github.com/yipersevere/age-estimation
공식 코드https://github.com/yjyddq/DLIF
공식 코드https://github.com/ykykyk112/STIG
공식 코드https://github.com/yl-1993/learn-to-cluster
공식 코드https://github.com/yliuaa/bnmr-faircompface
공식 코드https://github.com/ymx2022/3dfacetexture
공식 코드Self-supervised Re-renderable Facial Albedo Reconstruction from Single Image
https://github.com/yoctta/multiple-attention
공식 코드https://github.com/yongyizang/SingFake
공식 코드https://github.com/youngLBW/HRN
공식 코드https://github.com/youqingxiaozhua/apvit
공식 코드Vision Transformer with Attentive Pooling for Robust Facial Expression Recognition
https://github.com/yuangan/VidFace
공식 코드VidFace: A Full-Transformer Solver for Video FaceHallucination with Unaligned Tiny Snapshots
https://github.com/yuangan/eat_code
공식 코드Efficient Emotional Adaptation for Audio-Driven Talking-Head Generation
https://github.com/yuangan/silencer
공식 코드https://github.com/yuankaishen2001/Self-adjusting-AU
공식 코드Multi-scale Promoted Self-adjusting Correlation Learning for Facial Action Unit Detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.