MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversation

MMSA is a unified framework for Multimodal Sentiment Analysis.

An official implementation for " UniVL: A Unified Video and Language Pre-Training Model for Multimodal Understanding and Generation"

多模态情感分析——基于BERT+ResNet的多种融合方法

This repository contains the official implementation code of the paper Improving Multimodal Fusion with Hierarchical Mutual Information Maximization for Multimodal Sentiment Analysis, accepted at EMNLP 2021.

A Tool for extracting multimodal features from videos.

Context-Dependent Sentiment Analysis in User-Generated Videos

The code for our IEEE ACCESS (2020) paper Multimodal Emotion Recognition with Transformer-Based Self Supervised Feature Fusion.

CM-BERT: Cross-Modal BERT for Text-Audio Sentiment Analysis（MM2020）

Code for the paper "VistaNet: Visual Aspect Attention Network for Multimodal Sentiment Analysis", AAAI'19

Learning Language-guided Adaptive Hyper-modality Representation for Multimodal Sentiment Analysis

Offical implementation of paper "MSAF: Multimodal Split Attention Fusion"

This repository contains the implementation of the paper -- Bi-Bimodal Modality Fusion for Correlation-Controlled Multimodal Sentiment Analysis

A Facial Expression-Aware Multimodal Multi-task Learning Framework for Emotion Recognition in Multi-party Conversations (ACL 2023)

Multimodal sentiment analysis using hierarchical fusion with context modeling

Code and Data for the ACL22 main conference paper "MSCTD: A Multimodal Sentiment Chat Translation Dataset"

Towards Robust Multimodal Sentiment Analysis with Incomplete Data

NAACL 2022 paper on Analyzing Modality Robustness in Multimodal Sentiment Analysis

[EMNLP 2022] This repository contains the official implementation of the paper "MM-Align: Learning Optimal Transport-based Alignment Dynamics for Fast and Accurate Inference on Missing Modality Sequences"

DeepCU: Integrating Both Common and Unique Latent Information for Multimodal Sentiment Analysis, IJCAI-19