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fnhdx's Projects

ccnf icon ccnf

Libraries for training and testing Continuous Conditional Neural Fields with a number of sample problems and other baselines.

clm-framework icon clm-framework

CLM-framework (a.k.a Cambridge Face Tracker) is a framework for various Constrained Local Model based face tracking and landmark detection algorithms and their extensions/applications. Includes CLM-Z and CLNF.

cs-notes icon cs-notes

:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计、Java、Python、C++

cvpr15-cfss icon cvpr15-cfss

Full version (training+testing) of implementation of Shizhan Zhu et al.'s CVPR-15 work Face Alignment by Coarse-to-Fine Shape Searching

deeplabv3finetuning icon deeplabv3finetuning

Tutorial on fine tuning DeepLabv3 segmentation network for your own segmentation task in PyTorch.

detectron2 icon detectron2

Detectron2 is FAIR's next-generation platform for object detection, segmentation and other visual recognition tasks.

elsdc icon elsdc

Ellipse and Line Segment Detector, with Continuous validation

facekit icon facekit

Implementations of PCN (an accurate real-time rotation-invariant face detector) and other face-related algorithms

facialrelightingusing3dmodel icon facialrelightingusing3dmodel

Implementation for Face Relighting from a Single Image under Arbitrary Unknown Lighting Conditions (PAMI09) http://ieeexplore.ieee.org/document/4641935/

focal-loss-pytorch icon focal-loss-pytorch

全中文注释.(The loss function of retinanet based on pytorch).(You can use it on one-stage detection task or classifical task, to solve data imbalance influence).用于one-stage目标检测算法,提升检测效果.你也可以在分类任务中使用该损失函数,解决数据不平衡问题.

jvcr-3dlandmark icon jvcr-3dlandmark

Code for "Joint Voxel and Coordinate Regression for Accurate 3D Facial Landmark Localization"

mdm icon mdm

A TensorFlow implementation of the Mnemonic Descent Method.

mobilenetv2.pytorch icon mobilenetv2.pytorch

72.8% MobileNetV2 1.0 model on ImageNet and a spectrum of pre-trained MobileNetV2 models

openface icon openface

OpenFace – a state-of-the art tool intended for facial landmark detection, head pose estimation, facial action unit recognition, and eye-gaze estimation.

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