https://github.com/1adrianb/unsupervised-face-representation
공식 코드Pre-training strategies and datasets for facial representation learning
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/AaronJackson/vrn
공식 코드Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression
https://github.com/FuxiCV/3D-Face-GCNs
공식 코드https://github.com/FuxiCV/MeInGame
공식 코드MeInGame: Create a Game Character Face from a Single Portrait
https://github.com/Juyong/CaricatureFace
공식 코드Landmark Detection and 3D Face Reconstruction for Caricature using a Nonlinear Parametric Model
https://github.com/Juyong/FacePSNet
공식 코드https://github.com/LeiJiangJNU/DAMDNet
공식 코드Dual Attention MobDenseNet(DAMDNet) for Robust 3D Face Alignment
https://github.com/MCG-NJU/SADRNet
공식 코드https://github.com/Microsoft/Deep3DFaceReconstruction
공식 코드Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set
https://github.com/SCL-UT/face-manifold
공식 코드Face Manifold: Manifold Learning for Synthetic Face Generation
https://github.com/TimoBolkart/MultilinearWaveletModel
공식 코드Multilinear Wavelets: A Statistical Shape Space for Human Faces
https://github.com/TimoBolkart/TEMPEH
공식 코드Instant Multi-View Head Capture through Learnable Registration
https://github.com/YadiraF/DECA
공식 코드Learning an Animatable Detailed 3D Face Model from In-The-Wild Images
https://github.com/YadiraF/PIXIE
공식 코드Collaborative Regression of Expressive Bodies using Moderation
https://github.com/YadiraF/PRNet
공식 코드Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network
https://github.com/Zielon/MICA
공식 코드https://github.com/aashishrai3799/Towards-Realistic-Generative-3D-Face-Models
공식 코드https://github.com/anhttran/extreme_3d_faces
공식 코드https://github.com/arctrinity9/datasets-reachocc-and-synchocc
공식 코드Self-Supervised Robustifying Guidance for Monocular 3D Face Reconstruction
https://github.com/barisgecer/ganfit
공식 코드GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction
https://github.com/billyxyb/facednerf
공식 코드FaceDNeRF: Semantics-Driven Face Reconstruction, Prompt Editing and Relighting with Diffusion Models
https://github.com/billyxyb/fdnerf
공식 코드FaceDNeRF: Semantics-Driven Face Reconstruction, Prompt Editing and Relighting with Diffusion Models
https://github.com/cbsropenproject/6dof_face
공식 코드https://github.com/choyingw/SynergyNet
공식 코드Synergy between 3DMM and 3D Landmarks for Accurate 3D Facial Geometry
https://github.com/cleardusk/3DDFA_V2
공식 코드https://github.com/csbhr/ffhq-uv
공식 코드FFHQ-UV: Normalized Facial UV-Texture Dataset for 3D Face Reconstruction
https://github.com/cyj907/unsupervised-detail-layer
공식 코드https://github.com/czh-98/REALY
공식 코드https://github.com/deepinsight/insightface
공식 코드Perspective Reconstruction of Human Faces by Joint Mesh and Landmark Regression
https://github.com/face3d0725/face_de_mask
공식 코드https://github.com/facebookresearch/KeypointNeRF
공식 코드https://github.com/fdnerf/fdnerf
공식 코드FDNeRF: Few-shot Dynamic Neural Radiance Fields for Face Reconstruction and Expression Editing
https://github.com/fengju514/Expression-Net
공식 코드https://github.com/filby89/spectre
공식 코드Visual Speech-Aware Perceptual 3D Facial Expression Reconstruction from Videos
https://github.com/google/tf_mesh_renderer
공식 코드https://github.com/haoxin917/3dface
공식 코드3D Face Reconstruction Using A Spectral-Based Graph Convolution Encoder
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.