https://github.com/jiaxiangshang/MGCNet
공식 코드Self-Supervised Monocular 3D Face Reconstruction by Occlusion-Aware Multi-view Geometry Consistency
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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>
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Self-Supervised Monocular 3D Face Reconstruction by Occlusion-Aware Multi-view Geometry Consistency
AvatarMe: Realistically Renderable 3D Facial Reconstruction "in-the-wild"
DSFNet: Dual Space Fusion Network for Occlusion-Robust 3D Dense Face Alignment
FaceVerse: a Fine-grained and Detail-controllable 3D Face Morphable Model from a Hybrid Dataset
Unrestricted Facial Geometry Reconstruction Using Image-to-Image Translation
MobileFace: 3D Face Reconstruction with Efficient CNN Regression
3D Face Reconstruction Error Decomposed: A Modular Benchmark for Fair and Fast Method Evaluation
Robust Model-based Face Reconstruction through Weakly-Supervised Outlier Segmentation
Monocular Expressive Body Regression through Body-Driven Attention
3D Face Reconstruction with the Geometric Guidance of Facial Part Segmentation
From 2D Images to 3D Model:Weakly Supervised Multi-View Face Reconstruction with Deep Fusion
Self-supervised Re-renderable Facial Albedo Reconstruction from Single Image
FaceScape: 3D Facial Dataset and Benchmark for Single-View 3D Face Reconstruction
RAFaRe: Learning Robust and Accurate Non-parametric 3D Face Reconstruction from Pseudo 2D&3D Pairs
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
Facial Key Points Detection using Deep Convolutional Neural Network - NaimishNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.