Real-time video emotion recognition based on reinforcement learning and domain knowledge
Multimodal emotion recognition in conversational videos (ERC) develops rapidly in recent
years. To fully extract the relative context from video clips, most studies build their models on …
years. To fully extract the relative context from video clips, most studies build their models on …
Learning facial expression and body gesture visual information for video emotion recognition
Recent research has shown that facial expressions and body gestures are two significant
implications in identifying human emotions. However, these studies mainly focus on …
implications in identifying human emotions. However, these studies mainly focus on …
User-generated video emotion recognition based on key frames
J Wei, X Yang, Y Dong - Multimedia Tools and Applications, 2021 - Springer
Video is an important medium in communication and entertainment, and thus, an intelligent
understanding of videos has attracted widespread interest in academic community. Video …
understanding of videos has attracted widespread interest in academic community. Video …
Emonets: Multimodal deep learning approaches for emotion recognition in video
The task of the Emotion Recognition in the Wild (EmotiW) Challenge is to assign one of
seven emotions to short video clips extracted from Hollywood style movies. The videos …
seven emotions to short video clips extracted from Hollywood style movies. The videos …
Audio-visual emotion recognition using deep transfer learning and multiple temporal models
X Ouyang, S Kawaai, EGH Goh, S Shen… - Proceedings of the 19th …, 2017 - dl.acm.org
This paper presents the techniques used in our contribution to Emotion Recognition in the
Wild 2017 video based sub-challenge. The purpose of the sub-challenge is to classify the …
Wild 2017 video based sub-challenge. The purpose of the sub-challenge is to classify the …
An end-to-end visual-audio attention network for emotion recognition in user-generated videos
Emotion recognition in user-generated videos plays an important role in human-centered
computing. Existing methods mainly employ traditional two-stage shallow pipeline, ie …
computing. Existing methods mainly employ traditional two-stage shallow pipeline, ie …
M2fnet: Multi-modal fusion network for emotion recognition in conversation
V Chudasama, P Kar, A Gudmalwar… - Proceedings of the …, 2022 - openaccess.thecvf.com
Abstract Emotion Recognition in Conversations (ERC) is crucial in developing sympathetic
human-machine interaction. In conversational videos, emotion can be present in multiple …
human-machine interaction. In conversational videos, emotion can be present in multiple …
Video-based emotion recognition using CNN-RNN and C3D hybrid networks
In this paper, we present a video-based emotion recognition system submitted to the EmotiW
2016 Challenge. The core module of this system is a hybrid network that combines recurrent …
2016 Challenge. The core module of this system is a hybrid network that combines recurrent …
Multiple spatio-temporal feature learning for video-based emotion recognition in the wild
The difficulty of emotion recognition in the wild (EmotiW) is how to train a robust model to
deal with diverse scenarios and anomalies. The Audio-video Sub-challenge in EmotiW …
deal with diverse scenarios and anomalies. The Audio-video Sub-challenge in EmotiW …
Mimamo net: Integrating micro-and macro-motion for video emotion recognition
Spatial-temporal feature learning is of vital importance for video emotion recognition.
Previous deep network structures often focused on macro-motion which extends over long …
Previous deep network structures often focused on macro-motion which extends over long …