MMSA is a unified framework for Multimodal Sentiment Analysis.

MISA: Modality-Invariant and -Specific Representations for Multimodal Sentiment Analysis

ESANet: Efficient RGB-D Semantic Segmentation for Indoor Scene Analysis

[NeurIPS 2021] Multiscale Benchmarks for Multimodal Representation Learning

Pytorch implementation to paper "DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in Conversation".

This repo contains implementation of different architectures for emotion recognition in conversations.

A preprocessing and training code for DialogueGCN on Dailydialogue and Mastodon dataset. Use Bert base to preprocess the sentences. Based on https://github.com/declare-lab/conv-emotion/tree/master/…

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