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abaw2

audio-vidual attention fusion

abaw2-fpnmaa

Submission to ABAW2 Competition: Feature Pyramid Network for Multi-task Affective Analysis

abaw4

ECCV Workshop

ada-cm_semi_supervised_fer

“Towards Semi-Supervised Deep Facial Expression Recognition with An Adaptive Confidence Margin”, CVPR 2022.

afartoolbox

AFAR: A Deep Learning Based Toolbox for Automated Facial Affect Recognition

algorithm

Algorithm practice

awesome-embeded-ai

收集关于嵌入式领域的机器学习算法实现的进展、相关论文和文章、开发库等，帮助初学者快速了解、学习和入门嵌入式领域的机器学习。CC-BY-NC-SA 4.0。

awesome-multi-task-learning

A list of multi-task learning papers and projects.

cd-fer-benchmark

Adversarial Graph Representation Adaptation for Cross-Domain Facial Expression Recognition (AGRA, ACM 2020, Oral)

challenge-condition-fer-dataset

This is our collected datasets for challenge condition facial expression recognition

convlstm_pytorch

Implementation of Convolutional LSTM in PyTorch.

deep-emotion

Facial Expression Recognition Using Attentional Convolutional Network, Pytorch implementation

deep-head-pose

:fire::fire: Deep Learning Head Pose Estimation using PyTorch.

emotion-fan

ICIP 2019: Frame Attention Networks for Facial Expression Recognition in Videos

end2end-multimodal-affect-recognition

This repository contains the code for our Information Fusion paper "End-to-end multimodal affect recognition in real-world environments"

epro-pnp

[CVPR 2022 Oral, Best Student Paper] EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation

face-alignment

:fire: 2D and 3D Face alignment library build using pytorch

facecycle

Learning Facial Representations from the Cycle-consistency of Face (ICCV 2021)

facelib

Face Analysis: Detection, Age Gender Estimation & Recognition

facenet-pytorch

Pretrained Pytorch face detection (MTCNN) and facial recognition (InceptionResnet) models

facescape

FaceScape: a Large-scale High Quality 3D Face Dataset and Detailed Riggable 3D Face Prediction (CVPR2020)

facial-expression-recognition.pytorch

A CNN based pytorch implementation on facial expression recognition (FER2013 and CK+), achieving 73.112% (state-of-the-art) in FER2013 and 94.64% in CK+ dataset

fer-addl

fer-cfnet

Code implementation of CFNet

fer-cmcnn

code for paper "Co-attentive multi-task convolutional neural network for facial expression recognition"

fer-crs-cont-soon

“CRS-CONT: A Well-Trained General Encoder for Facial Expression Analysis”, IEEE TIP 2022.

fer-diversified-facial-expression-recognition

fer-efficientface

“Robust Lightweight Facial Expression Recognition Network with Label Distribution Training”, AAAI 2021.

fer-erasing-attention-consistency

Official implementation of the ECCV2022 paper: Learn From All: Erasing Attention Consistency for Noisy Label Facial Expression Recognition

fer-ma-net

“Learning Deep Global Multi-scale and Local Attention Features for Facial Expression Recognition in the Wild”, TIP 2021.