79 citations · 99 across the 13 of their papers we have counts for
13 papers
MEDIC: A Multimodal Empathy Dataset in Counseling
Zhou'an_Zhu, Xin Li, Jicai Pan +4
Although empathic interaction between counselor and client is fundamental to success in the psychotherapeutic process, there are currently few datasets to aid a computational appro…
Emotional Reaction Intensity Estimation Based on Multimodal Data
Shangfei Wang, Jiaqiang Wu, Feiyi Zheng +6
This paper introduces our method for the Emotional Reaction Intensity (ERI) Estimation Challenge, in CVPR 2023: 5th Workshop and Competition on Affective Behavior Analysis in-the-w…
Facial Affective Behavior Analysis Method for 5th ABAW Competition
Shangfei Wang, Yanan Chang, Yi Wu +5
Facial affective behavior analysis is important for human-computer interaction. 5th ABAW competition includes three challenges from Aff-Wild2 database. Three common facial affectiv…
Multi-Task Learning for Emotion Descriptors Estimation at the fourth ABAW Challenge
Yanan Chang, Yi Wu, Xiangyu Miao +2
Facial valence/arousal, expression and action unit are related tasks in facial affective analysis. However, the tasks only have limited performance in the wild due to the various c…
Hand-Assisted Expression Recognition Method from Synthetic Images at the Fourth ABAW Challenge
Xiangyu Miao, Jiahe Wang, Yanan Chang +2
Learning from synthetic images plays an important role in facial expression recognition task due to the difficulties of labeling the real images, and it is challenging because of t…
Facial Action Unit Recognition Based on Transfer Learning
Shangfei Wang, Yanan Chang, Jiahe Wang
Facial action unit recognition is an important task for facial analysis. Owing to the complex collection environment, facial action unit recognition in the wild is still challengin…
Exploring Adversarial Learning for Deep Semi-Supervised Facial Action Unit Recognition
Shangfei Wang, Yanan Chang, Guozhu Peng +1
Current works formulate facial action unit (AU) recognition as a supervised learning problem, requiring fully AU-labeled facial images during training. It is challenging if not imp…
Pose-aware Adversarial Domain Adaptation for Personalized Facial Expression Recognition
Guang Liang, Shangfei Wang, Can Wang
Current facial expression recognition methods fail to simultaneously cope with pose and subject variations. In this paper, we propose a novel unsupervised adversarial domain adapta…
Attentive One-Dimensional Heatmap Regression for Facial Landmark Detection and Tracking
Shi Yin, Shangfei Wang, Xiaoping Chen +1
Although heatmap regression is considered a state-of-the-art method to locate facial landmarks, it suffers from huge spatial complexity and is prone to quantization error. To addre…
Multiple Face Analyses through Adversarial Learning
Shangfei Wang, Shi Yin, Longfei Hao +1
This inherent relations among multiple face analysis tasks, such as landmark detection, head pose estimation, gender recognition and face attribute estimation are crucial to boost…
Affective Computing for Large-Scale Heterogeneous Multimedia Data: A Survey
Sicheng Zhao, Shangfei Wang, Mohammad Soleymani +2
The wide popularity of digital photography and social networks has generated a rapidly growing volume of multimedia data (i.e., image, music, and video), resulting in a great deman…
KDSL: a Knowledge-Driven Supervised Learning Framework for Word Sense Disambiguation
Shi Yin, Yi Zhou, Chenguang Li +4
We propose KDSL, a new word sense disambiguation (WSD) framework that utilizes knowledge to automatically generate sense-labeled data for supervised learning. First, from WordNet,…
Learning with Privileged Information for Multi-Label Classification
Shiyu Chen, Shangfei Wang, Tanfang Chen +1
In this paper, we propose a novel approach for learning multi-label classifiers with the help of privileged information. Specifically, we use similarity constraints to capture the…