no code implementations • 7 Dec 2023 • Qiuxiao Chen, Xiaojun Qi
In this paper, we propose to incorporate a novel Residual Graph Convolutional (RGC) module in deep CNNs to acquire both the global information and the region-level semantic relationship in the multi-view image domain.
1 code implementation • 18 Oct 2023 • Soheila Farokhi, Aswani Yaramala, Jiangtao Huang, Muhammad F. A. Khan, Xiaojun Qi, Hamid Karimi
However, current automated assessment approaches overlook the structural links between different entities involved in the downstream tasks, such as the students and courses.
1 code implementation • 7 Jan 2021 • Amir Hossein Farzaneh, Xiaojun Qi
Learning discriminative features for Facial Expression Recognition (FER) in the wild using Convolutional Neural Networks (CNNs) is a non-trivial task due to the significant intra-class variations and inter-class similarities.
Ranked #16 on Facial Expression Recognition (FER) on RAF-DB (using extra training data)
Facial Expression Recognition Facial Expression Recognition (FER) +2
no code implementations • 18 Feb 2019 • Mohammadreza Javanmardi, Amir Hossein Farzaneh, Xiaojun Qi
Sparse representation has recently been successfully applied in visual tracking.
no code implementations • 17 Feb 2019 • Mohammadreza Javanmardi, Xiaojun Qi
Sparse representation is considered as a viable solution to visual tracking.
no code implementations • 6 Jun 2018 • Mohammadreza Javanmardi, Xiaojun Qi
Specifically, we extract features of the target candidates from different views and sparsely represent them by a linear combination of templates of different views.