xlggzzz Goto Github PK

a2summ

The official implementation of 'Align and Attend: Multimodal Summarization with Dual Contrastive Losses' (CVPR 2023)

absa-reading-list

Reading list of aspect-based sentiment analysis.

acformer

acm-mm

adamf-mat

[Paper][LREC-COLING 2024] Unleashing the Power of Imbalanced Modality Information for Multi-modal Knowledge Graph Completion

adaptive-fusion-techniques-for-multimodal-data

Philo: uniting modalities

almt

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

amoa

arkmsa

This is the repository for our paper entitled with Enhancing Multimodal Sentiment Analysis via Learning from Large Language Model

awesome-mixture-of-experts

A collection of AWESOME things about mixture-of-experts

ch-sims-v2

Make Acoustic and Visual Cues Matter: CH-SIMS v2.0 Dataset and AV-Mixup Consistent Module

clmlf

cmu-multimodalsdk

confede

conference-acceptance-rate

Acceptance rates for the major AI conferences

cubemlp

The implementation of CubeMLP

dmd

An official implementation of "Decoupled Multimodal Distilling for Emotion Recognition" in PyTorch. (CVPR 2023 highlight)

dynmm

Code for the paper 'Dynamic Multimodal Fusion'

emmr

Mitigating Inconsistencies in Multimodal Sentiment Analysis under Uncertain Missing Modalities, in EMNLP2022

explainable-multimodal-emotion-reasoning

Official code and paper of "Explainable Multimodal Emotion Reasoning"

fafm

ECAI

fdt

gitdb

hgraph-cl

Code for COLING 2022 paper: Modeling Intra- and Inter-Modal Relations: Hierarchical Graph Contrastive Learning for Multimodal Sentiment Analysis

hkemodel

The formal

kamv

A Knowledge Augmented and Multimodal-Based Framework for Video Summarization

khanhnd185.github.io

m2-transformer-for-japanese

[PyTorch] Meshed-Memory Transformer for Japanese (日本語で学習・推論)

m3net

Pytorch implementation for the paper: Multivariate, Multi-frequency and Multimodal: Rethinking Graph Neural Networks for Emotion Recognition in Conversation, CVPR 2023.

mecpe

[TAFFC 2022] Multimodal Emotion-Cause Pair Extraction in Conversations