1 code implementation • 12 Mar 2024 • Chunlong Xia, Xinliang Wang, Feng Lv, Xin Hao, Yifeng Shi
Compared to the state-of-the-art, ViT-CoMer has the following advantages: (1) We inject spatial pyramid multi-receptive field convolutional features into the ViT architecture, which effectively alleviates the problems of limited local information interaction and single-feature representation in ViT.
1 code implementation • 22 Feb 2024 • Lianghui Zhu, Junwei Zhou, Yan Liu, Xin Hao, Wenyu Liu, Xinggang Wang
Weakly supervised visual recognition using inexact supervision is a critical yet challenging learning problem.
no code implementations • 23 Dec 2023 • Xin Hao, Changyang She, Phee Lep Yeoh, Yuhong Liu, Branka Vucetic, Yonghui Li
To enable the generalization of the GNN, we develop a hybrid-task meta-learning (HML) algorithm that trains the initial parameters of the GNN with different communication scenarios during meta-training.
no code implementations • 13 Dec 2023 • Xin Hao, Phee Lep Yeoh, Changyang She, Branka Vucetic, Yonghui Li
Our designed constrained DRL effectively attains the optimal resource allocations that are adapted to the dynamic DoS requirements.
no code implementations • 13 Dec 2023 • Xin Hao, Phee Lep Yeoh, Yuhong Liu, Changyang She, Branka Vucetic, Yonghui Li
This paper designs a graph neural network (GNN) to improve bandwidth allocations for multiple legitimate wireless users transmitting to a base station in the presence of an eavesdropper.
1 code implementation • CVPR 2023 • Haibao Yu, Wenxian Yang, Hongzhi Ruan, Zhenwei Yang, Yingjuan Tang, Xu Gao, Xin Hao, Yifeng Shi, Yifeng Pan, Ning Sun, Juan Song, Jirui Yuan, Ping Luo, Zaiqing Nie
Utilizing infrastructure and vehicle-side information to track and forecast the behaviors of surrounding traffic participants can significantly improve decision-making and safety in autonomous driving.
1 code implementation • 3 Oct 2021 • Laila Rasmy, Jie Zhu, Zhiheng Li, Xin Hao, Hong Thoai Tran, Yujia Zhou, Firat Tiryaki, Yang Xiang, Hua Xu, Degui Zhi
As a result, deep learning models developed for sequence modeling, like recurrent neural networks (RNNs) are common architecture for EHR-based clinical events predictive models.
no code implementations • ICCV 2021 • Xin Hao, Sanyuan Zhao, Mang Ye, Jianbing Shen
Cross-modality person re-identification is a challenging task due to large cross-modality discrepancy and intra-modality variations.
Cross-Modality Person Re-identification Person Re-Identification