From September 27, 2019, all future readings will be recorded in the document. Because I will graduate soon, there are many things to do, so the update is slow. After a period of time, I will organize all papers in a large scale during my graduate study
1、ICON: Interactive Conversational Memory Network for Multimodal Emotion Detection https://www.aclweb.org/anthology/D18-1280
2、Context-Dependent Sentiment Analysis in User-Generated Videos (ACL 2017).
3、Multi-level Multiple Attentions for Contextual Multimodal Sentiment Analysis(ICDM 2017).
Code for 2、3:https://github.com/SenticNet/multimodal-fusion
4、Tensor Fusion Network for Multimodal Sentiment Analysis(EMNLP 2017)
Code for 4:https://github.com/Justin1904/TensorFusionNetworks
5、Multimodal Transformer for Unaligned Multimodal Language Sequences(ACL 2019)
Code for 5:https://github.com/yaohungt/Multimodal-Transformer
6、Memory Fusion Network for Multi-view Sequential Learning(AAAI 2018)
Code for 6:https://github.com/pliang279/MFN
7、FACTORIZED MULTIMODAL TRANSFORMER FOR MULTIMODAL SEQUENTIAL LEARNING
Code for 7:https://github.com/A2Zadeh/Factorized-Multimodal-Transformer(release April 15th, 2020)
8、Multimodal Transformer for Unaligned Multimodal Language Sequences(ACL 2019)
Code for 8:https://github.com/yaohungt/Multimodal-Transformer
9、Multimodal Sentiment Analysis using Hierarchical Fusion with Context Modeling
Code for 9:https://github.com/SenticNet/hfusion
10、Found in Translation: Learning Robust Joint Representations by Cyclic Translations Between Modalities(2019 AAAI)
Code for 10:https://github.com/hainow/MCTN
11、Words Can Shift:Dynamically AdjustingWord Representations Using Nonverbal Behaviors(2019 AAAI)
Code for 11:https://github.com/victorywys/RAVEN
12、A Transformer-based joint-encoding for Emotion Recognition and Sentiment Analysis(2020 ACL workshop)
Code for 12:https://github.com/jbdel/MOSEI_UMONS
13、Low Rank Fusion based Transformers for Multimodal Sequences(2020 ACL workshop)
14、Quantum Cognitively Motivated Decision Fusion for Video Sentiment Analysis(AAAI2021)
15、Learning Modality-Specific Representations with Self-Supervised Multi-Task Learning for Multimodal Sentiment Analysis(AAAI2021)
16、Quantum Cognitively Motivated Decision Fusion for Video Sentiment Analysis(AAAI2021)
17、An Entanglement-driven Fusion Neural Network for Video Sentiment Analysis(IJCAI2021)
18、Quantum-inspired Neural Network for Conversational Emotion Recognition(AAAI2021)
1、VideoBERT: A Joint Model for Video and Language Representation Learning (ICCV2019)
2、ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks (NeurIPS2019)
3、VisualBERT: A Simple and Performant Baseline for Vision and Language
4、Selfie: Self-supervised Pretraining for Image Embedding
5、Contrastive Bidirectional Transformer for Temporal Representation Learning
6、M-BERT: Injecting Multimodal Information in the BERT Structure
7、LXMERT: Learning Cross-Modality Encoder Representations from Transformers (EMNLP2019)
8、Fusion of Detected Objects in Text for Visual Question Answering (EMNLP2019)
9、Unified Vision-Language Pre-Training for Image Captioning and VQA
Code for 9：https://github.com/LuoweiZhou/VLP
10、VL-BERT: Pre-training of Generic Visual-Linguistic Representations
11、Unicoder-VL: A Universal Encoder for Vision and Language by Cross-modal Pre-training
12、UNITER: Learning UNiversal Image-TExt Representations
13、SpeechBERT: Cross-Modal Pre-trained Language Model for End-to-end Spoken Question Answering
14、Multimodal Transformer for Unaligned Multimodal Language Sequences
Code for 14:https://github.com/yaohungt/Multimodal-Transformer
15、Integrating Multimodal Information in Large Pretrained Transformers(2020 ACL)
Code for 15:https://github.com/WasifurRahman/BERT_multimodal_transformer
16、CM-BERT: Cross-Modal BERT for Text-Audio Sentiment Analysis(2020 ACMMM，ours)
Code for 16:https://github.com/thuiar/Cross-Modal-BERT
1、Attention-augmented end-to-end multi-task learning for emotion prediction from speech.
https://arxiv.org/pdf/1903.12424.pdf
2、Multi-task Learning for Multi-modal Emotion Recognition and Sentiment Analysis.
https://arxiv.org/pdf/1905.05812.pdf
3、Multi-task Learning for Target-dependent Sentiment Classification.
https://arxiv.org/pdf/1902.02930.pdf
4、Sentiment and Sarcasm Classification with Multitask Learning.
https://sentic.net/sentiment-and-sarcasm-classification-with-multitask-learning.pdf
1、SMIL: Multimodal Learning with Severely Missing Modality(2021 AAAI)
Code for 1:https://github.com/mengmenm/SMIL