56 citations · 129 across the 7 of their papers we have counts for
7 papers
MAC 2026: Advancing Micro-Action Analysis Towards Fine-Grained Understanding
Kun Li, Dan Guo, Jihao Gu +6
Micro-Actions (MAs) are subtle and spontaneous human behaviors that provide important non-verbal cues in social interaction and affective communication. However, their short durati…
Linguistics-Vision Monotonic Consistent Network for Sign Language Production
Xu Wang, Shengeng Tang, Peipei Song +3
Sign Language Production (SLP) aims to generate sign videos corresponding to spoken language sentences, where the conversion of sign Glosses to Poses (G2P) is the key step. Due to…
PsycoLLM: Enhancing LLM for Psychological Understanding and Evaluation
Jinpeng Hu, Tengteng Dong, Luo Gang +6
Mental health has attracted substantial attention in recent years and LLM can be an effective technology for alleviating this problem owing to its capability in text understanding…
Exploiting Diverse Feature for Multimodal Sentiment Analysis
Jia Li, Wei Qian, Kun Li +3
In this paper, we present our solution to the MuSe-Personalisation sub-challenge in the MuSe 2023 Multimodal Sentiment Analysis Challenge. The task of MuSe-Personalisation aims to…
MEGCF: Multimodal Entity Graph Collaborative Filtering for Personalized Recommendation
Kang Liu, Feng Xue, Dan Guo +3
In most E-commerce platforms, whether the displayed items trigger the user's interest largely depends on their most eye-catching multimodal content. Consequently, increasing effort…
Joint Multi-grained Popularity-aware Graph Convolution Collaborative Filtering for Recommendation
Kang Liu, Feng Xue, Xiangnan He +2
Graph Convolution Networks (GCNs), with their efficient ability to capture high-order connectivity in graphs, have been widely applied in recommender systems. Stacking multiple nei…
Emotion Separation and Recognition from a Facial Expression by Generating the Poker Face with Vision Transformers
Jia Li, Jiantao Nie, Dan Guo +2
Representation learning and feature disentanglement have garnered significant research interest in the field of facial expression recognition (FER). The inherent ambiguity of emoti…