https://github.com/zyh-uaiaaaa/erasing-attention-consistency
공식 코드Learn From All: Erasing Attention Consistency for Noisy Label Facial Expression Recognition
Papers with Code 아카이브
Facial Expression Recognition (FER)
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 5
- 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/zyh-uaiaaaa/generalizable-fer
공식 코드https://github.com/zyzhangustc/mellm
공식 코드MELLM: Exploring LLM-Powered Micro-Expression Understanding Enhanced by Subtle Motion Perception
https://bitbucket.org/nishkalavallabhi/complexity-features
Readability-based Sentence Ranking for Evaluating Text Simplification
https://github.com/1chenchen22/LFNSB
https://github.com/2023-MindSpore-4/Code8/tree/main/cct
https://github.com/AdrianVG194/cnn-hyperopt-fer2013
https://github.com/AmirSh15/FECNet
https://github.com/AmrElsersy/Emotions-Recognition
https://github.com/Conero007/Emotion-Detection-Pytorch
Challenges in Representation Learning: A report on three machine learning contests
https://github.com/ElenaRyumina/EMO-AffectNetModel
https://github.com/EverLookNeverSee/fer_tl_dcnn
https://github.com/GerardLiu96/FECNet
https://github.com/Hamiedamr/EmotionNet-Nano-An-Efficient-Deep-Convolutional-Neural-Network-Design-for-Real-time-Facial-Expressi
https://github.com/IcedDoggie/Micro-Expression-with-Deep-Learning
Enriched Long-term Recurrent Convolutional Network for Facial Micro-Expression Recognition
https://github.com/KLT20/Realtime-Face-Emotion-Recognition
Deep-Emotion: Facial Expression Recognition Using Attentional Convolutional Network
https://github.com/LetheSec/Fer2013-Facial-Emotion-Recognition-Pytorch
https://github.com/MaxLikesMath/DeepLearningImplementations
DeXpression: Deep Convolutional Neural Network for Expression Recognition
https://github.com/MindSpore-paper-code-3/code6/tree/main/cct
https://github.com/NJNischal/Facial-Expression-Recognition-with-CNNs
Challenges in Representation Learning: A report on three machine learning contests
https://github.com/NPilis/Facial-Expression-Recognition
https://github.com/NathanHouwaart/EmotionRecognition
Training Deep Networks for Facial Expression Recognition with Crowd-Sourced Label Distribution
https://github.com/OmarEl-Khashab/FerNeXt-Facial-Expression-Recognition-Using-ConvNeXt-with-Channel-Attention
https://github.com/RainbowRui/Landmark-Driven-Facial-Expression-Recognition
Suppressing Uncertainties for Large-Scale Facial Expression Recognition
https://github.com/Recognito-Vision/Linux-FaceRecognition-FaceLivenessDetection
https://github.com/SeongwoongJo/Multimodal-Emotional-Recognition
Frame attention networks for facial expression recognition in videos
https://github.com/ShiqiYu/libfacedetection
https://github.com/ShuvenduRoy/FER_TL_PipelineTraining
https://github.com/VigneshS10/Segmentation-VGG19
https://github.com/WhiTExB3AR/Emotion_Diary
Facial Motion Prior Networks for Facial Expression Recognition
https://github.com/WhiTExB3AR/PreProduceCode-FMPN-FER
Facial Motion Prior Networks for Facial Expression Recognition
https://github.com/ZBigFish/FER-VT
https://github.com/aliprf/Ad-Corre
https://github.com/amirhfarzaneh/dacl
https://github.com/anshu123priya/Real-v-s-Fake-Emotion-Challenge
MicroExpNet: An Extremely Small and Fast Model For Expression Recognition From Face Images
https://github.com/anshu123priya/Real-vs-Fake-Emotion-Challenge
MicroExpNet: An Extremely Small and Fast Model For Expression Recognition From Face Images
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.