https://github.com/anitagold/30-days-of-Udacity
Facial Key Points Detection using Deep Convolutional Neural Network - NaimishNet
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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.
Facial Key Points Detection using Deep Convolutional Neural Network - NaimishNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
Cross-modal Deep Face Normals with Deactivable Skip Connections
Perspective Reconstruction of Human Faces by Joint Mesh and Landmark Regression
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
Cross-Modal Perceptionist: Can Face Geometry be Gleaned from Voices?
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
Unrestricted Facial Geometry Reconstruction Using Image-to-Image Translation
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
Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network
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
Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network
Facial Key Points Detection using Deep Convolutional Neural Network - NaimishNet
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
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
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.