57 citations · 105 across the 9 of their papers we have counts for
9 papers · 1 filter
Correlation-Aware Deep Tracking
Fei Xie, Chunyu Wang, Guangting Wang +3
Robustness and discrimination power are two fundamental requirements in visual object tracking. In most tracking paradigms, we find that the features extracted by the popular Siame…
When Shift Operation Meets Vision Transformer: An Extremely Simple Alternative to Attention Mechanism
Guangting Wang, Yucheng Zhao, Chuanxin Tang +2
Attention mechanism has been widely believed as the key to success of vision transformers (ViTs), since it provides a flexible and powerful way to model spatial relationships. Howe…
Learning Tracking Representations via Dual-Branch Fully Transformer Networks
Fei Xie, Chunyu Wang, Guangting Wang +2
We present a Siamese-like Dual-branch network based on solely Transformers for tracking. Given a template and a search image, we divide them into non-overlapping patches and extrac…
Sparse MLP for Image Recognition: Is Self-Attention Really Necessary?
Chuanxin Tang, Yucheng Zhao, Guangting Wang +3
Transformers have sprung up in the field of computer vision. In this work, we explore whether the core self-attention module in Transformer is the key to achieving excellent perfor…
Self-Supervised Visual Representations Learning by Contrastive Mask Prediction
Yucheng Zhao, Guangting Wang, Chong Luo +2
Advanced self-supervised visual representation learning methods rely on the instance discrimination (ID) pretext task. We point out that the ID task has an implicit semantic consis…
A Battle of Network Structures: An Empirical Study of CNN, Transformer, and MLP
Yucheng Zhao, Guangting Wang, Chuanxin Tang +3
Convolutional neural networks (CNN) are the dominant deep neural network (DNN) architecture for computer vision. Recently, Transformer and multi-layer perceptron (MLP)-based models…
Unsupervised Visual Representation Learning by Tracking Patches in Video
Guangting Wang, Yizhou Zhou, Chong Luo +3
Inspired by the fact that human eyes continue to develop tracking ability in early and middle childhood, we propose to use tracking as a proxy task for a computer vision system to…
Tracking by Instance Detection: A Meta-Learning Approach
Guangting Wang, Chong Luo, Xiaoyan Sun +2
We consider the tracking problem as a special type of object detection problem, which we call instance detection. With proper initialization, a detector can be quickly converted in…
SPM-Tracker: Series-Parallel Matching for Real-Time Visual Object Tracking
Guangting Wang, Chong Luo, Zhiwei Xiong +1
The greatest challenge facing visual object tracking is the simultaneous requirements on robustness and discrimination power. In this paper, we propose a SiamFC-based tracker, name…