2019-2013表情识别推荐论文

转：

https://blog.youkuaiyun.com/qq_32528489/article/details/81672247

https://cloud.tencent.com/developer/article/1366761

2018 年 

1. Facial Expression Recognition by De-expression Residue Learning （CVPR）
2. Joint Pose and Expression Modeling for Facial Expression Recognition （CVPR）
3. A Compact Deep Learning Model for Robust Facial Expression Recognition （CVPR）

2017 年 

1. Identity-aware convolutional neural network for facial expression recognition （In Automatic Face & Gesture Recognition (FG 2017)） 

2. Facenet2expnet: Regularizing a deep face recognition net for expression recognition（In Automatic Face & Gesture Recognition (FG 2017)） 
3. Facial expression recognition with convolutional neural networks: Coping with few data and the training sample order. (Pattern Recognition) 

2016 年 

1. Peak-piloted deep network for facial expression Recognition (ECCV) 
2. Lomo: Latent ordinal model for facial analysis in videos ( arXiv) 
3. How deep neural networks can improve emotion recognition on video data (ICIP) 
4. A deep neural network-driven feature learning method for multi-view facial expression recognition （TMM） 

2015 年 

1. Joint fine-tuning in deep neural networks for facial expression recognition （ICCV） 
2. Automatic 3d facial expression recognition using geometric scattering representation （In Automatic Face & Gesture Recognition (FG 2017)） 
3. An efficient multimodal 2d+ 3d feature-based approach to automatic facial expression recognition. (Computer Vision and Image Understanding) 
4. Multi-view facial expressions recognition using local linear regression of sparse codes (In Computer Vision Winter Workshop Paul Wohlhart) 
5. Exemplar hidden markov models for classification of facial expressions in videos (CVPR) 

2014 年 

1. Learning expressionlets on spatio-temporal manifold for dynamic facial expression recognition (CVPR) 
2. Facial expression recognition via a boosted deep belief network (CVPR) 
3. Supervised super-vector encoding for facial expression recognition 
4. Multi-view facial expression recognition based 
5. on group sparse reduced-rank regression （TAC） 
6. Learning expressionlets on spatio-temporal manifold for dynamic facial expression recognition （CVPR） 
7. Deeply learning deformable facial action parts model for dynamic expression analysis （In Asian Conference on Computer Vision） 

2013 年 

1. Maximum margin gmm learning for facial expression recognition （FG）