23 citations · 47 across the 24 of their papers we have counts for
11 papers · 1 filter
Mamba-Enhanced Text-Audio-Video Alignment Network for Emotion Recognition in Conversations
Xinran Li, Xiaomao Fan, Qingyang Wu +2
Emotion Recognition in Conversations (ERCs) is a vital area within multimodal interaction research, dedicated to accurately identifying and classifying the emotions expressed by sp…
DPDEdit: Detail-Preserved Diffusion Models for Multimodal Fashion Image Editing
Xiaolong Wang, Zhi-Qi Cheng, Jue Wang +1
Fashion image editing is a crucial tool for designers to convey their creative ideas by visualizing design concepts interactively. Current fashion image editing techniques, though…
Multimodal Multi-turn Conversation Stance Detection: A Challenge Dataset and Effective Model
Fuqiang Niu, Zebang Cheng, Xianghua Fu +5
Stance detection, which aims to identify public opinion towards specific targets using social media data, is an important yet challenging task. With the proliferation of diverse mu…
SZTU-CMU at MER2024: Improving Emotion-LLaMA with Conv-Attention for Multimodal Emotion Recognition
Zebang Cheng, Shuyuan Tu, Dawei Huang +4
This paper presents our winning approach for the MER-NOISE and MER-OV tracks of the MER2024 Challenge on multimodal emotion recognition. Our system leverages the advanced emotional…
FlexEdit: Marrying Free-Shape Masks to VLLM for Flexible Image Editing
Tianshuo Yuan, Yuxiang Lin, Jue Wang +5
Combining Vision Large Language Models (VLLMs) with diffusion models offers a powerful method for executing image editing tasks based on human language instructions. However, langu…
DSMix: Distortion-Induced Sensitivity Map Based Pre-training for No-Reference Image Quality Assessment
Jinsong Shi, Pan Gao, Xiaojiang Peng +1
Image quality assessment (IQA) has long been a fundamental challenge in image understanding. In recent years, deep learning-based IQA methods have shown promising performance. Howe…
Emotion-LLaMA: Multimodal Emotion Recognition and Reasoning with Instruction Tuning
Zebang Cheng, Zhi-Qi Cheng, Jun-Yan He +6
Accurate emotion perception is crucial for various applications, including human-computer interaction, education, and counseling. However, traditional single-modality approaches of…
MIPS at SemEval-2024 Task 3: Multimodal Emotion-Cause Pair Extraction in Conversations with Multimodal Language Models
Zebang Cheng, Fuqiang Niu, Yuxiang Lin +3
This paper presents our winning submission to Subtask 2 of SemEval 2024 Task 3 on multimodal emotion cause analysis in conversations. We propose a novel Multimodal Emotion Recognit…
UMETTS: A Unified Framework for Emotional Text-to-Speech Synthesis with Multimodal Prompts
Zhi-Qi Cheng, Xiang Li, Jun-Yan He +4
Emotional Text-to-Speech (E-TTS) synthesis has garnered significant attention in recent years due to its potential to revolutionize human-computer interaction. However, current E-T…
A Challenge Dataset and Effective Models for Conversational Stance Detection
Fuqiang Niu, Min Yang, Ang Li +3
Previous stance detection studies typically concentrate on evaluating stances within individual instances, thereby exhibiting limitations in effectively modeling multi-party discus…
Invisible Gas Detection: An RGB-Thermal Cross Attention Network and A New Benchmark
Jue Wang, Yuxiang Lin, Qi Zhao +4
The widespread use of various chemical gases in industrial processes necessitates effective measures to prevent their leakage during transportation and storage, given their high to…