5 papers · 1 filter
AffectGPT-RL: Revealing Roles of Reinforcement Learning in Open-Vocabulary Emotion Recognition
Zheng Lian, Fan Zhang, Lan Chen +8
Open-Vocabulary Multimodal Emotion Recognition (OV-MER) aims to predict emotions without being constrained by predefined label spaces, thereby enabling fine-grained emotion underst…
AffectGPT-R1: Leveraging Reinforcement Learning for Open-Vocabulary Multimodal Emotion Recognition
Zheng Lian, Fan Zhang, Yazhou Zhang +5
Open-Vocabulary Multimodal Emotion Recognition (OV-MER) aims to predict emotions without being constrained by label spaces, enabling fine-grained emotion understanding. Unlike trad…
EmoPrefer: Can Large Language Models Understand Human Emotion Preferences?
Zheng Lian, Licai Sun, Lan Chen +8
Descriptive Multimodal Emotion Recognition (DMER) has garnered increasing research attention. Unlike traditional discriminative paradigms that rely on predefined emotion taxonomies…
AffectGPT: A New Dataset, Model, and Benchmark for Emotion Understanding with Multimodal Large Language Models
Zheng Lian, Haoyu Chen, Lan Chen +9
The emergence of multimodal large language models (MLLMs) advances multimodal emotion recognition (MER) to the next level, from naive discriminative tasks to complex emotion unders…
OV-MER: Towards Open-Vocabulary Multimodal Emotion Recognition
Zheng Lian, Haiyang Sun, Licai Sun +13
Multimodal Emotion Recognition (MER) is a critical research area that seeks to decode human emotions from diverse data modalities. However, existing machine learning methods predom…