activity
20182022
most citedGLMNet: Graph Learning-Matching Networks for Feature Matching

23 citations · 38 across the 13 of their papers we have counts for

collaborators

30 papers

cs.CV2021

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…

cs.CV2021

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…

cs.CV20212 cited

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…

cs.CV20204 cited

Viewpoint-aware Progressive Clustering for Unsupervised Vehicle Re-identification

Aihua Zheng, Xia Sun, Chenglong Li +1

Vehicle re-identification (Re-ID) is an active task due to its importance in large-scale intelligent monitoring in smart cities. Despite the rapid progress in recent years, most ex…

cs.CV2020

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…

cs.CV20201 cited

Challenge-Aware RGBT Tracking

Chenglong Li, Lei Liu, Andong Lu +2

RGB and thermal source data suffer from both shared and specific challenges, and how to explore and exploit them plays a critical role to represent the target appearance in RGBT tr…