1 code implementation • 20 Jan 2024 • Haoxiang Yang, Chengguo Yuan, Yabin Zhu, Lan Chen, Xiao Wang, Jin Tang
The mainstream human activity recognition (HAR) algorithms are developed based on RGB cameras, which are easily influenced by low-quality images (e. g., low illumination, motion blur).
1 code implementation • 5 Jan 2024 • Yabin Zhu, Xiao Wang, Chenglong Li, Bo Jiang, Lin Zhu, Zhixiang Huang, Yonghong Tian, Jin Tang
In this work, we formally propose the task of object tracking using unaligned neuromorphic and visible cameras.
no code implementations • 26 Mar 2023 • Yabin Zhu, Chenglong Li, Xiao Wang, Jin Tang, Zhixiang Huang
In addition, existing learning methods of RGBT trackers either fuse multimodal features into one for final classification, or exploit the relationship between unimodal branches and fused branch through a competitive learning strategy.
1 code implementation • 11 Feb 2022 • Yabin Zhu, Chenglong Li, Yao Liu, Xiao Wang, Jin Tang, Bin Luo, Zhixiang Huang
Tiny objects, frequently appearing in practical applications, have weak appearance and features, and receive increasing interests in meany vision tasks, such as object detection and segmentation.
no code implementations • 12 Aug 2019 • Rui Yang, Yabin Zhu, Xiao Wang, Chenglong Li, Jin Tang
RGB-Thermal object tracking attempt to locate target object using complementary visual and thermal infrared data.
no code implementations • 24 Jul 2019 • Yabin Zhu, Chenglong Li, Bin Luo, Jin Tang, Xiao Wang
In different modalities, we propose to prune the densely aggregated features of all modalities in a collaborative way.
no code implementations • 24 Nov 2018 • Yabin Zhu, Chenglong Li, Bin Luo, Jin Tang
This paper investigates how to perform robust visual tracking in adverse and challenging conditions using complementary visual and thermal infrared data (RGBT tracking).