23 citations · 43 across the 8 of their papers we have counts for
18 papers · 1 filter
Tracking by Joint Local and Global Search: A Target-aware Attention based Approach
Xiao Wang, Jin Tang, Bin Luo +3
Tracking-by-detection is a very popular framework for single object tracking which attempts to search the target object within a local search window for each frame. Although such l…
Dynamic Attention guided Multi-Trajectory Analysis for Single Object Tracking
Xiao Wang, Zhe Chen, Jin Tang +4
Most of the existing single object trackers track the target in a unitary local search window, making them particularly vulnerable to challenging factors such as heavy occlusions a…
PICA: A Pixel Correlation-based Attentional Black-box Adversarial Attack
Jie Wang, Zhaoxia Yin, Jin Tang +2
The studies on black-box adversarial attacks have become increasingly prevalent due to the intractable acquisition of the structural knowledge of deep neural networks (DNNs). Howev…
RGBT Tracking via Multi-Adapter Network with Hierarchical Divergence Loss
Andong Lu, Chenglong Li, Yuqing Yan +2
RGBT tracking has attracted increasing attention since RGB and thermal infrared data have strong complementary advantages, which could make trackers all-day and all-weather work. H…
GmCN: Graph Mask Convolutional Network
Bo Jiang, Beibei Wang, Jin Tang +1
Graph Convolutional Networks (GCNs) have shown very powerful for graph data representation and learning tasks. Existing GCNs usually conduct feature aggregation on a fixed neighbor…
GLMNet: Graph Learning-Matching Networks for Feature Matching
Bo Jiang, Pengfei Sun, Jin Tang +1
Recently, graph convolutional networks (GCNs) have shown great potential for the task of graph matching. It can integrate graph node feature embedding, node-wise affinity learning…