HyperAI超神经
首页资讯最新论文教程数据集百科SOTALLM 模型天梯GPU 天梯顶会
全站搜索
关于
HyperAI超神经

3D Face Reconstruction On Florence

评估指标

Mean NME

评测结果

各个模型在此基准测试上的表现结果

模型名称
Mean NME
Paper TitleRepository
VRN-Guided5.2667%Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression
Piotraschke and Blanz-Automated 3D Face Reconstruction From Multiple Images Using Quality Measures-
DenseLandmarks (Single-view)-3D face reconstruction with dense landmarks-
3DDFA_V2-Towards Fast, Accurate and Stable 3D Dense Face Alignment
Deep3DFaceReconstruction-Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set
Tran et al.-Regressing Robust and Discriminative 3D Morphable Models with a very Deep Neural Network
DenseLandmarks (Multi-view)-3D face reconstruction with dense landmarks-
GANFit-GANFIT: Generative Adversarial Network Fitting for High Fidelity 3D Face Reconstruction
itwmm-3D Face Morphable Models "In-the-Wild"-
ASM-ASM: Adaptive Skinning Model for High-Quality 3D Face Modeling-
3DDFA6.3833%Face Alignment Across Large Poses: A 3D Solution-
3DMM-CNN-Regressing Robust and Discriminative 3D Morphable Models with a very Deep Neural Network
PRN3.7551%Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network
Deng-Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set
Unsupervised-3DMMR-Unsupervised Training for 3D Morphable Model Regression
Genova et al.-Unsupervised Training for 3D Morphable Model Regression
0 of 16 row(s) selected.