49 citations · 184 across the 11 of their papers we have counts for
12 papers
Video Annotation for Visual Tracking via Selection and Refinement
Kenan Dai, Jie Zhao, Lijun Wang +5
Deep learning based visual trackers entail offline pre-training on large volumes of video datasets with accurate bounding box annotations that are labor-expensive to achieve. We pr…
A Video Is Worth Three Views: Trigeminal Transformers for Video-based Person Re-identification
Xuehu Liu, Pingping Zhang, Chenyang Yu +3
Video-based person re-identification (Re-ID) aims to retrieve video sequences of the same person under non-overlapping cameras. Previous methods usually focus on limited views, suc…
Watching You: Global-guided Reciprocal Learning for Video-based Person Re-identification
Xuehu Liu, Pingping Zhang, Chenyang Yu +2
Video-based person re-identification (Re-ID) aims to automatically retrieve video sequences of the same person under non-overlapping cameras. To achieve this goal, it is the key to…
Transformer Tracking
Xin Chen, Bin Yan, Jiawen Zhu +3
Correlation acts as a critical role in the tracking field, especially in recent popular Siamese-based trackers. The correlation operation is a simple fusion manner to consider the…
Alpha-Refine: Boosting Tracking Performance by Precise Bounding Box Estimation
Bin Yan, Xinyu Zhang, Dong Wang +2
Visual object tracking aims to precisely estimate the bounding box for the given target, which is a challenging problem due to factors such as deformation and occlusion. Many recen…
Jointly Modeling Motion and Appearance Cues for Robust RGB-T Tracking
Pengyu Zhang, Jie Zhao, Dong Wang +2
In this study, we propose a novel RGB-T tracking framework by jointly modeling both appearance and motion cues. First, to obtain a robust appearance model, we develop a novel late…
Alpha-Refine: Boosting Tracking Performance by Precise Bounding Box Estimation
Bin Yan, Dong Wang, Huchuan Lu +1
In recent years, the multiple-stage strategy has become a popular trend for visual tracking. This strategy first utilizes a base tracker to coarsely locate the target and then expl…
High-Performance Long-Term Tracking with Meta-Updater
Kenan Dai, Yunhua Zhang, Dong Wang +3
Long-term visual tracking has drawn increasing attention because it is much closer to practical applications than short-term tracking. Most top-ranked long-term trackers adopt the…
Cooling-Shrinking Attack: Blinding the Tracker with Imperceptible Noises
Bin Yan, Dong Wang, Huchuan Lu +1
Adversarial attack of CNN aims at deceiving models to misbehave by adding imperceptible perturbations to images. This feature facilitates to understand neural networks deeply and t…
GradNet: Gradient-Guided Network for Visual Object Tracking
Peixia Li, Boyu Chen, Wanli Ouyang +3
The fully-convolutional siamese network based on template matching has shown great potentials in visual tracking. During testing, the template is fixed with the initial target feat…
'Skimming-Perusal' Tracking: A Framework for Real-Time and Robust Long-term Tracking
Bin Yan, Haojie Zhao, Dong Wang +2
Compared with traditional short-term tracking, long-term tracking poses more challenges and is much closer to realistic applications. However, few works have been done and their pe…
Cascaded Context Pyramid for Full-Resolution 3D Semantic Scene Completion
Pingping Zhang, Wei Liu, Yinjie Lei +2
Semantic Scene Completion (SSC) aims to simultaneously predict the volumetric occupancy and semantic category of a 3D scene. It helps intelligent devices to understand and interact…