1 code implementation • 20 Jan 2024 • Yuefang Gao, Yuhao Xie, Zeke Zexi Hu, Tianshui Chen, Liang Lin
Specifically, the framework consists of separate global-local adversarial learning modules that learn domain-invariant global and local features independently.
Cross-Domain Facial Expression Recognition Model Optimization +2
1 code implementation • 20 Apr 2022 • Ling Huang, Can-Rong Guan, Zhen-Wei Huang, Yuefang Gao, Yingjie Kuang, Chang-Dong Wang, C. L. Philip Chen
Recently, Deep Neural Networks (DNNs) have been widely introduced into Collaborative Filtering (CF) to produce more accurate recommendation results due to their capability of capturing the complex nonlinear relationships between items and users. However, the DNNs-based models usually suffer from high computational complexity, i. e., consuming very long training time and storing huge amount of trainable parameters.
1 code implementation • 14 Aug 2018 • Tianshui Chen, Wenxi Wu, Yuefang Gao, Le Dong, Xiaonan Luo, Liang Lin
In this work, we investigate simultaneously predicting categories of different levels in the hierarchy and integrating this structured correlation information into the deep neural network by developing a novel Hierarchical Semantic Embedding (HSE) framework.
Ranked #52 on Fine-Grained Image Classification on CUB-200-2011
Fine-Grained Image Classification Fine-Grained Image Recognition +1
1 code implementation • 1 Mar 2016 • Zexi Hu, Yuefang Gao, Dong Wang, Xuhong Tian
Given a base tracker, an ensemble of trackers is generated, in which each tracker's update behavior will be paced and then traces the target object forward and backward to generate a pair of trajectories in an interval.