1 code implementation • 16 Mar 2022 • Jun Wang, Ying Cui, Dongyan Guo, Junxia Li, Qingshan Liu, Chunhua Shen
To solve the problems, we leverage the cross-attention and self-attention mechanisms to design novel neural network for processing point cloud in a per-point manner to eliminate kNNs.
no code implementations • 23 Jun 2021 • Jialing Liu, Ruyu Liu, Kaiqi Chen, Jianhua Zhang, Dongyan Guo
Each agent can independently explore the environment, run a visual-inertial odometry module online, and then send all the measurement information to a central server with higher computing resources.
no code implementations • CVPR 2021 • Dongyan Guo, Yanyan Shao, Ying Cui, Zhenhua Wang, Liyan Zhang, Chunhua Shen
We propose to establish part-to-part correspondence between the target and the search region with a complete bipartite graph, and apply the graph attention mechanism to propagate target information from the template feature to the search feature.
1 code implementation • ICCV 2021 • Zhenhua Wang, Jiajun Meng, Dongyan Guo, Jianhua Zhang, Javen Qinfeng Shi, ShengYong Chen
Compared with the progress made on human activity classification, much less success has been achieved on human interaction understanding (HIU).
no code implementations • 3 Jul 2020 • Miao Tian, Dongyan Guo, Ying Cui, Xiang Pan, Sheng-Yong Chen
Novelty detection is a important research area which mainly solves the classification problem of inliers which usually consists of normal samples and outliers composed of abnormal samples.
2 code implementations • CVPR 2020 • Dongyan Guo, Jun Wang, Ying Cui, Zhenhua Wang, Sheng-Yong Chen
The proposed framework SiamCAR consists of two simple subnetworks: one Siamese subnetwork for feature extraction and one classification-regression subnetwork for bounding box prediction.
no code implementations • 4 Feb 2019 • Dongyan Guo, Jun Wang, Weixuan Zhao, Ying Cui, Zhenhua Wang, Sheng-Yong Chen
Both features and the channel weights are utilized in a template generation layer to generate a discriminative template.