https://github.com/av-savchenko/emotiefflib
Frame-level Prediction of Facial Expressions, Valence, Arousal and Action Units for Mobile Devices
Papers with Code 아카이브
Facial Expression Recognition (FER)
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
- 25
- 보존된 평가 기록
- 167
Facial Expression Recognition (FER) is a computer vision task aimed at identifying and categorizing emotional expressions depicted on a human face. The goal is to automate the process of determining emotions in real-time, by analyzing the various features of a face such as eyebrows, eyes, mouth, and other features, and mapping them to a set of emotions such as anger, fear, surprise, sadness and happiness.
<span style="color:grey; opacity: 0.6">( Image credit: DeXpression )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/azadlab/FExGAN-Meta
https://github.com/bakerv/fer-webcam
Facial Emotion Recognition: State of the Art Performance on FER2013
https://github.com/behzadhsni/BReG-NeXt
BReG-NeXt: Facial Affect Computing Using Adaptive Residual Networks With Bounded Gradient
https://github.com/bogireddytejareddy/micro-expression-recognition
https://github.com/cem8301/EmotionDetector
https://github.com/chinhau-lim/fer2013
Challenges in Representation Learning: A report on three machine learning contests
https://github.com/chinhau-lim/fer_2013
Challenges in Representation Learning: A report on three machine learning contests
https://github.com/christy1206/STSTNet
Shallow Triple Stream Three-dimensional CNN (STSTNet) for Micro-expression Recognition
https://github.com/ckapoor7/DeXpression
DeXpression: Deep Convolutional Neural Network for Expression Recognition
https://github.com/cuguilke/microexpnet
MicroExpNet: An Extremely Small and Fast Model For Expression Recognition From Face Images
https://github.com/derek-baker/group3
Spotting Macro- and Micro-expression Intervals in Long Video Sequences
https://github.com/elangarka/Regularized-Xception-FER-Extra-Training-Data-Step-Decay-Learning-Rate
Challenges in Representation Learning: A report on three machine learning contests
https://github.com/eric-erki/Visualising-Facial-Expression-Changes
https://github.com/fulviomascara/pytorch-cv
Facial Expression Recognition Research Based on Deep Learning
https://github.com/hemanshanand/Facial-Expression-Recognition
Challenges in Representation Learning: A report on three machine learning contests
https://github.com/holman57/AI_Emotion_Detection
Training Deep Networks for Facial Expression Recognition with Crowd-Sourced Label Distribution
https://github.com/iiTzFrankie/DCJT
https://github.com/ivclab/PAE
https://github.com/jannine92/supervised_emotion_recognition
Challenges in Representation Learning: A report on three machine learning contests
https://github.com/jason90330/EdgeFinal
Learning to Amend Facial Expression Representation via De-albino and Affinity
https://github.com/jaydeepthik/kaggle-facial-expression-recognition
Convolutional Neural Networks for Facial Expression Recognition
https://github.com/jiangxingxun/Seeking_Salient_Facial_Region
Seeking Salient Facial Regions for Cross-Database Micro-Expression Recognition
https://github.com/jiantenggei/Convolutional-Neural-Network-Hyperparameters-Optimization-for-Facial-Emotion-Recognition
https://github.com/jonathangiguere/Emotion_Image_Classifier
AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild
https://github.com/justinshenk/fer
Challenges in Representation Learning: A report on three machine learning contests
https://github.com/kaushal-k/Deep-Emotion
Deep-Emotion: Facial Expression Recognition Using Attentional Convolutional Network
https://github.com/kyranstar/Narcissus
https://github.com/leorrose/Facial-Expression-Recognition
Challenges in Representation Learning: A report on three machine learning contests
https://github.com/leorrose/Social-Network-Facial-Expression-Recognition
Challenges in Representation Learning: A report on three machine learning contests
https://github.com/mg515/lie-detektor
Enriched Long-term Recurrent Convolutional Network for Facial Micro-Expression Recognition
https://github.com/mkonuk66/EfficientFER
https://github.com/modelhub-ai/emotion-fer-plus
Training Deep Networks for Facial Expression Recognition with Crowd-Sourced Label Distribution
https://github.com/negarhdr/skeleton-based-action-recognition
https://github.com/oellop/facial_expression
Challenges in Representation Learning: A report on three machine learning contests
https://github.com/omarsayed7/Deep-Emotion
Deep-Emotion: Facial Expression Recognition Using Attentional Convolutional Network
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.