168 citations · 359 across the 17 of their papers we have counts for
17 papers
Multi-Granularity Graph Pooling for Video-based Person Re-Identification
Honghu Pan, Yongyong Chen, Zhenyu He
The video-based person re-identification (ReID) aims to identify the given pedestrian video sequence across multiple non-overlapping cameras. To aggregate the temporal and spatial…
SSORN: Self-Supervised Outlier Removal Network for Robust Homography Estimation
Yi Li, Wenjie Pei, Zhenyu He
The traditional homography estimation pipeline consists of four main steps: feature detection, feature matching, outlier removal and transformation estimation. Recent deep learning…
Global Tracking via Ensemble of Local Trackers
Zikun Zhou, Jianqiu Chen, Wenjie Pei +3
The crux of long-term tracking lies in the difficulty of tracking the target with discontinuous moving caused by out-of-view or occlusion. Existing long-term tracking methods follo…
GuidedMix-Net: Semi-supervised Semantic Segmentation by Using Labeled Images as Reference
Peng Tu, Yawen Huang, Feng Zheng +3
Semi-supervised learning is a challenging problem which aims to construct a model by learning from limited labeled examples. Numerous methods for this task focus on utilizing the p…
Active Learning for Deep Visual Tracking
Di Yuan, Xiaojun Chang, Yi Yang +3
Convolutional neural networks (CNNs) have been successfully applied to the single target tracking task in recent years. Generally, training a deep CNN model requires numerous label…
Saliency-Associated Object Tracking
Zikun Zhou, Wenjie Pei, Xin Li +3
Most existing trackers based on deep learning perform tracking in a holistic strategy, which aims to learn deep representations of the whole target for localizing the target. It is…
SiamCorners: Siamese Corner Networks for Visual Tracking
Kai Yang, Zhenyu He, Wenjie Pei +4
The current Siamese network based on region proposal network (RPN) has attracted great attention in visual tracking due to its excellent accuracy and high efficiency. However, the…
TCDesc: Learning Topology Consistent Descriptors for Image Matching
Honghu Pan, Fanyang Meng, Nana Fan +1
The constraint of neighborhood consistency or local consistency is widely used for robust image matching. In this paper, we focus on learning neighborhood topology consistent descr…
LSOTB-TIR:A Large-Scale High-Diversity Thermal Infrared Object Tracking Benchmark
Qiao Liu, Xin Li, Zhenyu He +8
In this paper, we present a Large-Scale and high-diversity general Thermal InfraRed (TIR) Object Tracking Benchmark, called LSOTBTIR, which consists of an evaluation dataset and a…
Accurate Bounding-box Regression with Distance-IoU Loss for Visual Tracking
Di Yuan, Xiu Shu, Nana Fan +3
Most existing trackers are based on using a classifier and multi-scale estimation to estimate the target state. Consequently, and as expected, trackers have become more stable whil…
TCDesc: Learning Topology Consistent Descriptors
Honghu Pan, Fanyang Meng, Zhenyu He +2
Triplet loss is widely used for learning local descriptors from image patch. However, triplet loss only minimizes the Euclidean distance between matching descriptors and maximizes…
Multi-Task Driven Feature Models for Thermal Infrared Tracking
Qiao Liu, Xin Li, Zhenyu He +4
Existing deep Thermal InfraRed (TIR) trackers usually use the feature models of RGB trackers for representation. However, these feature models learned on RGB images are neither eff…
Learning Deep Multi-Level Similarity for Thermal Infrared Object Tracking
Qiao Liu, Xin Li, Zhenyu He +3
Existing deep Thermal InfraRed (TIR) trackers only use semantic features to describe the TIR object, which lack the sufficient discriminative capacity for handling distractors. Thi…
Target-Aware Deep Tracking
Xin Li, Chao Ma, Baoyuan Wu +2
Existing deep trackers mainly use convolutional neural networks pre-trained for generic object recognition task for representations. Despite demonstrated successes for numerous vis…
Region-filtering Correlation Tracking
Nana Fan, Zhenyu He
Recently, correlation filters have demonstrated the excellent performance in visual tracking. However, the base training sample region is larger than the object region,including th…
PTB-TIR: A Thermal Infrared Pedestrian Tracking Benchmark
Qiao Liu, Zhenyu He, Xin Li +1
Thermal infrared (TIR) pedestrian tracking is one of the important components among numerous applications of computer vision, which has a major advantage: it can track pedestrians…
Hierarchical Spatial-aware Siamese Network for Thermal Infrared Object Tracking
Xin Li, Qiao Liu, Nana Fan +2
Most thermal infrared (TIR) tracking methods are discriminative, treating the tracking problem as a classification task. However, the objective of the classifier (label prediction)…