Papers with Code 아카이브
3D Face Reconstruction
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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/cleardusk/MFR
공식 코드https://github.com/cleardusk/MeGlass
공식 코드https://github.com/clferrari/facepartsswap
공식 코드What makes you, you? Analyzing Recognition by Swapping Face Parts
https://github.com/clks-wzz/FAS-SGTD
공식 코드Deep Spatial Gradient and Temporal Depth Learning for Face Anti-spoofing
https://github.com/clks-wzz/epcr
공식 코드https://github.com/clovaai/EXTD_Pytorch
공식 코드EXTD: Extremely Tiny Face Detector via Iterative Filter Reuse
https://github.com/clovaai/eresfd
공식 코드EResFD: Rediscovery of the Effectiveness of Standard Convolution for Lightweight Face Detection
https://github.com/clpeng/Awesome-Face-Forgery-Generation-and-Detection
공식 코드Countering Malicious DeepFakes: Survey, Battleground, and Horizon
https://github.com/cmry/reap
공식 코드Adversarial Stylometry in the Wild: Transferable Lexical Substitution Attacks on Author Profiling
https://github.com/cnnlstm/fslsd_hires
공식 코드High-resolution Face Swapping via Latent Semantics Disentanglement
https://github.com/controlnet/av-deepfake1m
공식 코드AV-Deepfake1M: A Large-Scale LLM-Driven Audio-Visual Deepfake Dataset
https://github.com/coolEphemeroptera/AESRC2020
공식 코드https://github.com/crane-papercode/ICE-GAN
공식 코드https://github.com/croitorualin/biodeep
공식 코드Deepfake Media Generation and Detection in the Generative AI Era: A Survey and Outlook
https://github.com/cruiseyugh/gus
공식 코드https://github.com/crusnic-corp/BN-AuthProf
공식 코드BN-AuthProf: Benchmarking Machine Learning for Bangla Author Profiling on Social Media Texts
https://github.com/crywang/RFM
공식 코드https://github.com/csbhr/ffhq-uv
공식 코드FFHQ-UV: Normalized Facial UV-Texture Dataset for 3D Face Reconstruction
https://github.com/csehong/SSPP-DAN
공식 코드SSPP-DAN: Deep Domain Adaptation Network for Face Recognition with Single Sample Per Person
https://github.com/csinva/matching-with-gans
공식 코드Matched sample selection with GANs for mitigating attribute confounding
https://github.com/csong27/ml-model-remember
공식 코드https://github.com/csxmli2016/SymmFCNet
공식 코드https://github.com/csyxwei/FFWM
공식 코드https://github.com/cutz-j/FDFtNet
공식 코드FDFtNet: Facing Off Fake Images using Fake Detection Fine-tuning Network
https://github.com/cvgmi/nestedgrassmann
공식 코드Nested Grassmannians for Dimensionality Reduction with Applications
https://github.com/cvi-szu/degstalk
공식 코드DEGSTalk: Decomposed Per-Embedding Gaussian Fields for Hair-Preserving Talking Face Synthesis
https://github.com/cvi-szu/mdhr
공식 코드Multi-scale Dynamic and Hierarchical Relationship Modeling for Facial Action Units Recognition
https://github.com/cvi-szu/me-graphau
공식 코드Learning Multi-dimensional Edge Feature-based AU Relation Graph for Facial Action Unit Recognition
https://github.com/cyf-cuber/mol
공식 코드https://github.com/cyj907/unsupervised-detail-layer
공식 코드https://github.com/cyjie429/rego
공식 코드Region-Based Optimization in Continual Learning for Audio Deepfake Detection
https://github.com/czh-98/REALY
공식 코드https://github.com/d-acharya/CovPoolFER
공식 코드https://github.com/daizigege/Identity_hider
공식 코드Seeing is not Believing: An Identity Hider for Human Vision Privacy Protection
https://github.com/damo-cv/mogface
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.