Emotion Recognition

442 papers with code • 7 benchmarks • 44 datasets

Emotion Recognition is an important area of research to enable effective human-computer interaction. Human emotions can be detected using speech signal, facial expressions, body language, and electroencephalography (EEG). Source: Using Deep Autoencoders for Facial Expression Recognition

Most implemented papers

Complementary Fusion of Multi-Features and Multi-Modalities in Sentiment Analysis

robertjkeck2/EmoTe 17 Apr 2019

Therefore, in this paper, based on audio and text, we consider the task of multimodal sentiment analysis and propose a novel fusion strategy including both multi-feature fusion and multi-modality fusion to improve the accuracy of audio-text sentiment analysis.

Multitask Emotion Recognition with Incomplete Labels

wtomin/Multitask-Emotion-Recognition-with-Incomplete-Labels 10 Feb 2020

We use the soft labels and the ground truth to train the student model.

Context Based Emotion Recognition using EMOTIC Dataset

rkosti/emotic 30 Mar 2020

In this paper we present EMOTIC, a dataset of images of people in a diverse set of natural situations, annotated with their apparent emotion.

Compact Graph Architecture for Speech Emotion Recognition

AmirSh15/Compact_SER 5 Aug 2020

We propose a deep graph approach to address the task of speech emotion recognition.

MER 2023: Multi-label Learning, Modality Robustness, and Semi-Supervised Learning

zeroqiaoba/mer2023-baseline 18 Apr 2023

The first Multimodal Emotion Recognition Challenge (MER 2023) was successfully held at ACM Multimedia.

Building a Large Scale Dataset for Image Emotion Recognition: The Fine Print and The Benchmark

noahj08/DeepConnotation 9 May 2016

We hope that this data set encourages further research on visual emotion analysis.

DAGER: Deep Age, Gender and Emotion Recognition Using Convolutional Neural Network

CVxTz/face_age_gender 14 Feb 2017

This paper describes the details of Sighthound's fully automated age, gender and emotion recognition system.

End-to-End Multimodal Emotion Recognition using Deep Neural Networks

tzirakis/Multimodal-Emotion-Recognition 27 Apr 2017

The system is then trained in an end-to-end fashion where - by also taking advantage of the correlations of the each of the streams - we manage to significantly outperform the traditional approaches based on auditory and visual handcrafted features for the prediction of spontaneous and natural emotions on the RECOLA database of the AVEC 2016 research challenge on emotion recognition.

Context-Dependent Sentiment Analysis in User-Generated Videos

senticnet/sc-lstm ACL 2017

Multimodal sentiment analysis is a developing area of research, which involves the identification of sentiments in videos.

EmoTxt: A Toolkit for Emotion Recognition from Text

collab-uniba/Emotion_and_Polarity_SO 13 Aug 2017

We provide empirical evidence of the performance of EmoTxt.