253 citations · 375 across the 12 of their papers we have counts for
12 papers
MAE-DFER: Efficient Masked Autoencoder for Self-supervised Dynamic Facial Expression Recognition
Licai Sun, Zheng Lian, Bin Liu +1
Dynamic facial expression recognition (DFER) is essential to the development of intelligent and empathetic machines. Prior efforts in this field mainly fall into supervised learnin…
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…
ADD 2023: the Second Audio Deepfake Detection Challenge
Jiangyan Yi, Jianhua Tao, Ruibo Fu +15
Audio deepfake detection is an emerging topic in the artificial intelligence community. The second Audio Deepfake Detection Challenge (ADD 2023) aims to spur researchers around the…
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…
VRA: Variational Rectified Activation for Out-of-distribution Detection
Mingyu Xu, Zheng Lian, Bin Liu +1
Out-of-distribution (OOD) detection is critical to building reliable machine learning systems in the open world. Researchers have proposed various strategies to reduce model overco…
ALIM: Adjusting Label Importance Mechanism for Noisy Partial Label Learning
Mingyu Xu, Zheng Lian, Lei Feng +2
Noisy partial label learning (noisy PLL) is an important branch of weakly supervised learning. Unlike PLL where the ground-truth label must conceal in the candidate label set, nois…
IRNet: Iterative Refinement Network for Noisy Partial Label Learning
Zheng Lian, Mingyu Xu, Lan Chen +4
Partial label learning (PLL) is a typical weakly supervised learning, where each sample is associated with a set of candidate labels. Its basic assumption is that the ground-truth…
An Overview of Affective Speech Synthesis and Conversion in the Deep Learning Era
Andreas Triantafyllopoulos, Björn W. Schuller, Gökçe İymen +9
Speech is the fundamental mode of human communication, and its synthesis has long been a core priority in human-computer interaction research. In recent years, machines have manage…
Efficient Multimodal Transformer with Dual-Level Feature Restoration for Robust Multimodal Sentiment Analysis
Licai Sun, Zheng Lian, Bin Liu +1
With the proliferation of user-generated online videos, Multimodal Sentiment Analysis (MSA) has attracted increasing attention recently. Despite significant progress, there are sti…
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…
Adaptive Pseudo-Siamese Policy Network for Temporal Knowledge Prediction
Pengpeng Shao, Tong Liu, Feihu Che +2
Temporal knowledge prediction is a crucial task for the event early warning that has gained increasing attention in recent years, which aims to predict the future facts by using re…
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…