128 citations · 387 across the 30 of their papers we have counts for
8 papers · 1 filter
Exploring Emotion Features and Fusion Strategies for Audio-Video Emotion Recognition
Hengshun Zhou, Debin Meng, Yuanyuan Zhang +4
The audio-video based emotion recognition aims to classify a given video into basic emotions. In this paper, we describe our approaches in EmotiW 2019, which mainly explores emotio…
Attention-Driven Dynamic Graph Convolutional Network for Multi-Label Image Recognition
Jin Ye, Junjun He, Xiaojiang Peng +2
Recent studies often exploit Graph Convolutional Network (GCN) to model label dependencies to improve recognition accuracy for multi-label image recognition. However, constructing…
AU-Guided Unsupervised Domain Adaptive Facial Expression Recognition
Kai Wang, Yuxin Gu, Xiaojiang Peng +3
The domain diversities including inconsistent annotation and varied image collection conditions inevitably exist among different facial expression recognition (FER) datasets, which…
Suppressing Mislabeled Data via Grouping and Self-Attention
Xiaojiang Peng, Kai Wang, Zhaoyang Zeng +3
Deep networks achieve excellent results on large-scale clean data but degrade significantly when learning from noisy labels. To suppressing the impact of mislabeled data, this pape…
Visual Compositional Learning for Human-Object Interaction Detection
Zhi Hou, Xiaojiang Peng, Yu Qiao +1
Human-Object interaction (HOI) detection aims to localize and infer relationships between human and objects in an image. It is challenging because an enormous number of possible co…
TTPP: Temporal Transformer with Progressive Prediction for Efficient Action Anticipation
Wen Wang, Xiaojiang Peng, Yanzhou Su +2
Video action anticipation aims to predict future action categories from observed frames. Current state-of-the-art approaches mainly resort to recurrent neural networks to encode hi…
Suppressing Uncertainties for Large-Scale Facial Expression Recognition
Kai Wang, Xiaojiang Peng, Jianfei Yang +2
Annotating a qualitative large-scale facial expression dataset is extremely difficult due to the uncertainties caused by ambiguous facial expressions, low-quality facial images, an…
A Comprehensive Study on Temporal Modeling for Online Action Detection
Wen Wang, Xiaojiang Peng, Yu Qiao +1
Online action detection (OAD) is a practical yet challenging task, which has attracted increasing attention in recent years. A typical OAD system mainly consists of three modules:…