activity
20222026
most citedSVFAP: Self-supervised Video Facial Affect Perceiver

29 citations · 59 across the 17 of their papers we have counts for

collaborators

17 papers

cs.SD2026

OV-InstructTTS: Towards Open-Vocabulary Instruct Text-to-Speech

Yong Ren, Jiangyan Yi, Jianhua Tao +5

Instruct Text-to-Speech (InstructTTS) leverages natural language descriptions as style prompts to guide speech synthesis. However, existing InstructTTS methods mainly rely on a dir…

cs.HC2025★ 2 cited

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…

cs.HC2024★ 1 cited

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…

cs.HC2024★ 2 cited

AffectGPT: Dataset and Framework for Explainable Multimodal Emotion Recognition

Zheng Lian, Haiyang Sun, Licai Sun +3

Explainable Multimodal Emotion Recognition (EMER) is an emerging task that aims to achieve reliable and accurate emotion recognition. However, due to the high annotation cost, the…

cs.LG2024★ 2 cited

MER 2024: Semi-Supervised Learning, Noise Robustness, and Open-Vocabulary Multimodal Emotion Recognition

Zheng Lian, Haiyang Sun, Licai Sun +15

Multimodal emotion recognition is an important research topic in artificial intelligence. Over the past few decades, researchers have made remarkable progress by increasing the dat…

cs.CV2024

Multimodal Fusion with Pre-Trained Model Features in Affective Behaviour Analysis In-the-wild

Zhuofan Wen, Fengyu Zhang, Siyuan Zhang +6

Multimodal fusion is a significant method for most multimodal tasks. With the recent surge in the number of large pre-trained models, combining both multimodal fusion methods and p…

cs.CL2024★ 1 cited

Can Deception Detection Go Deeper? Dataset, Evaluation, and Benchmark for Deception Reasoning

Kang Chen, Zheng Lian, Haiyang Sun +4

Deception detection has attracted increasing attention due to its importance in real-world scenarios. Its main goal is to detect deceptive behaviors from multimodal clues such as g…

cs.HC2024★ 6 cited

MERBench: A Unified Evaluation Benchmark for Multimodal Emotion Recognition

Zheng Lian, Licai Sun, Yong Ren +5

Multimodal emotion recognition plays a crucial role in enhancing user experience in human-computer interaction. Over the past few decades, researchers have proposed a series of alg…

cs.CV2024★ 29 cited

SVFAP: Self-supervised Video Facial Affect Perceiver

Licai Sun, Zheng Lian, Kexin Wang +5

Video-based facial affect analysis has recently attracted increasing attention owing to its critical role in human-computer interaction. Previous studies mainly focus on developing…

cs.MM2023★ 1 cited

ITEACH-Net: Inverted Teacher-studEnt seArCH Network for Emotion Recognition in Conversation

Haiyang Sun, Zheng Lian, Chenglong Wang +4

There remain two critical challenges that hinder the development of ERC. Firstly, there is a lack of exploration into mining deeper insights from the data itself for conversational…

cs.CV2023★ 3 cited

GPT-4V with Emotion: A Zero-shot Benchmark for Generalized Emotion Recognition

Zheng Lian, Licai Sun, Haiyang Sun +5

Recently, GPT-4 with Vision (GPT-4V) has demonstrated remarkable visual capabilities across various tasks, but its performance in emotion recognition has not been fully evaluated.…

cs.MM2023★ 9 cited

Explainable Multimodal Emotion Recognition

Zheng Lian, Haiyang Sun, Licai Sun +13

Multimodal emotion recognition is an important research topic in artificial intelligence, whose main goal is to integrate multimodal clues to identify human emotional states. Curre…

eess.AS2023★ 2 cited

MFSN: Multi-perspective Fusion Search Network For Pre-training Knowledge in Speech Emotion Recognition

Haiyang Sun, Fulin Zhang, Yingying Gao +3

Speech Emotion Recognition (SER) is an important research topic in human-computer interaction. Many recent works focus on directly extracting emotional cues through pre-trained kno…

cs.CL2023★ 1 cited

MER 2023: Multi-label Learning, Modality Robustness, and Semi-Supervised Learning

Zheng Lian, Haiyang Sun, Licai Sun +15

The first Multimodal Emotion Recognition Challenge (MER 2023) was successfully held at ACM Multimedia. The challenge focuses on system robustness and consists of three distinct tra…

cs.SD2022

Fully Automated End-to-End Fake Audio Detection

Chenglong Wang, Jiangyan Yi, Jianhua Tao +6

The existing fake audio detection systems often rely on expert experience to design the acoustic features or manually design the hyperparameters of the network structure. However,…

cs.CV2022

Two-Aspect Information Fusion Model For ABAW4 Multi-task Challenge

Haiyang Sun, Zheng Lian, Bin Liu +3

In this paper, we propose the solution to the Multi-Task Learning (MTL) Challenge of the 4th Affective Behavior Analysis in-the-wild (ABAW) competition. The task of ABAW is to pred…

eess.AS2022

EmotionNAS: Two-stream Neural Architecture Search for Speech Emotion Recognition

Haiyang Sun, Zheng Lian, Bin Liu +6

Speech emotion recognition (SER) is an important research topic in human-computer interaction. Existing works mainly rely on human expertise to design models. Despite their success…