300 citations · 1.2k across the 44 of their papers we have counts for
7 papers · 1 filter
Quality-Aware Multimodal Saliency Detection via Deep Reinforcement Learning
Xiao Wang, Tao Sun, Rui Yang +3
Incorporating various modes of information into the machine learning procedure is becoming a new trend. And data from various source can provide more information than single one no…
Describe and Attend to Track: Learning Natural Language guided Structural Representation and Visual Attention for Object Tracking
Xiao Wang, Chenglong Li, Rui Yang +3
The tracking-by-detection framework requires a set of positive and negative training samples to learn robust tracking models for precise localization of target objects. However, ex…
Graph Learning-Convolutional Networks
Bo Jiang, Ziyan Zhang, Doudou Lin +1
Recently, graph Convolutional Neural Networks (graph CNNs) have been widely used for graph data representation and semi-supervised learning tasks. However, existing graph CNNs gene…
FANet: Quality-Aware Feature Aggregation Network for Robust RGB-T Tracking
Yabin Zhu, Chenglong Li, Bin Luo +1
This paper investigates how to perform robust visual tracking in adverse and challenging conditions using complementary visual and thermal infrared data (RGBT tracking). We propose…
Graph Diffusion-Embedding Networks
Bo Jiang, Doudou Lin, Jin Tang
We present a novel graph diffusion-embedding networks (GDEN) for graph structured data. GDEN is motivated by our closed-form formulation on regularized feature diffusion on graph.…
RGB-T Object Tracking:Benchmark and Baseline
Chenglong Li, Xinyan Liang, Yijuan Lu +2
RGB-Thermal (RGB-T) object tracking receives more and more attention due to the strongly complementary benefits of thermal information to visible data. However, RGB-T research is l…
Temporal Coherent and Graph Optimized Manifold Ranking for Visual Tracking
Bo Jiang, Doudou Lin, Bin Luo +1
Recently, weighted patch representation has been widely studied for alleviating the impact of background information included in bounding box to improve visual tracking results. Ho…