winner-4

winner-4's Stars

• lxq1000/Faceptor

  Official implementation of Faceptor: A Generalist Model for Face Perception.

  Language:Python24

• trutadan/FER-project

  The emotion recognition methodology integrates precise face detection and landmark extraction using the SPIGA detector. Landmarks are then aligned by shifting centered on the nasal bridge, enhancing uniformity. Differences between neutral and expressive poses generate 98 feature vectors per emotion. These vectors train different classifiers.

  Language:Python1

• tegusi/EAGRNet

  Edge-aware Graph Representation Learning and Reasoning for Face Parsing (ECCV 2020)

  Language:Python12121

• av-savchenko/face-emotion-recognition

  Efficient face emotion recognition in photos and videos

  Language:Jupyter Notebook657124

• SainingZhang/DDAMFN

  Language:Python9015

• youqingxiaozhua/APViT

  PaddlePaddle and PyTorch implementation of APViT and TransFER

  Language:Python389

• WZMIAOMIAO/deep-learning-for-image-processing

  deep learning for image processing including classification and object-detection etc.

  Language:Python22.6k7.9k

• eraserNut/MTMT

  Code for the CVPR 2020 paper "A Multi-task Mean Teacher for Semi-supervised Shadow Detection"

  Language:Python10114

• a312863063/generators-with-stylegan2

  Here is a series of face generators based on StyleGAN2

  Language:Python2.4k552

• nomewang/MCF

  [MM 2023] Toward High Quality Facial Representation Learning

  Language:Python16

• dk-liang/TransCrowd

  [SCIS] TransCrowd: Weakly-Supervised Crowd Counting with Transformers

  Language:Python9417

• winner-4/project

  Language:Python1

• dilionb/croud_counting

  31

• TencentYoutuResearch/CrowdCounting-UEPNet

  The official codes for the ICCV2021 presentation "Uniformity in Heterogeneity: Diving Deep into Count Interval Partition for Crowd Counting"

  Language:Python247

• winner-4/Machine-Learning

  :zap:机器学习实战（Python3）：kNN、决策树、贝叶斯、逻辑回归、SVM、线性回归、树回归

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