70 citations · 107 across the 8 of their papers we have counts for
8 papers
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…
HiCMAE: Hierarchical Contrastive Masked Autoencoder for Self-Supervised Audio-Visual Emotion Recognition
Licai Sun, Zheng Lian, Bin Liu +1
Audio-Visual Emotion Recognition (AVER) has garnered increasing attention in recent years for its critical role in creating emotion-ware intelligent machines. Previous efforts in t…
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…
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…
Pseudo Labels Regularization for Imbalanced Partial-Label Learning
Mingyu Xu, Zheng Lian
Partial-label learning (PLL) is an important branch of weakly supervised learning where the single ground truth resides in a set of candidate labels, while the research rarely cons…
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…