Evolve to be more comprehensive, effective and efficient for face related analytics \& applications! (WeChat News) About the name: "face" means this repo is dedicated for face related analytics \& applications. "evolve" means unleash your greatness to be better and better. "LV" are capitalized…
Principalele funcționalități ale zhaoj9014/face.evolve.pytorch sunt: Face Analysis Libraries, Facial, Action and Pose Recognition.
Alternativele open-source pentru zhaoj9014/face.evolve.pytorch includ: aaltovision/dgc-net — A PyTorch implementation of "DGC-Net: Dense Geometric Correspondence Network". albertpumarola/ganimation — Official implementation of GANimation. In this work we introduce a novel GAN conditioning scheme based on Action Units… clcarwin/sphereface_pytorch. clementpinard/flownetpytorch — Pytorch implementation of FlowNet by Dosovitskiy et al. clementpinard/sfmlearner-pytorch — Pytorch version of SfmLearner from Tinghui Zhou et al. 1adrianb/face-alignment — This is a PyTorch-based computer vision library for detecting 2D and 3D facial landmark coordinates. It functions as a…
A PyTorch implementation of "DGC-Net: Dense Geometric Correspondence Network"
Official implementation of GANimation. In this work we introduce a novel GAN conditioning scheme based on Action Units (AU) annotations, which describe in a continuous manifold the anatomical facial movements defining a human expression. Our approach permits controlling the magnitude of…
This is a PyTorch-based computer vision library for detecting 2D and 3D facial landmark coordinates. It functions as a facial landmark detector and reconstruction tool, utilizing deep learning to identify precise geometric points on human faces from image datasets. The library allows for the selection of specific detection backends to balance accuracy and processing speed. It supports the integration of precomputed bounding box files, which enables the system to bypass the initial detection phase and proceed directly to landmark extraction. The toolkit includes capabilities for batch image p