Real-Time Visual Tracking
10 papers with code • 0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Real-Time Visual Tracking
Drunkard's Dataset
Latest papers with no code
Towards Real-Time Visual Tracking with Graded Color-names Features
MeanShift algorithm has been widely used in tracking tasks because of its simplicity and efficiency.
DCF-ASN: Coarse-to-fine Real-time Visual Tracking via Discriminative Correlation Filter and Attentional Siamese Network
Discriminative correlation filters (DCF) and siamese networks have achieved promising performance on visual tracking tasks thanks to their superior computational efficiency and reliable similarity metric learning, respectively.
Object-Adaptive LSTM Network for Real-time Visual Tracking with Adversarial Data Augmentation
This strategy efficiently filters out some irrelevant proposals and avoids the redundant computation for feature extraction, which enables our method to operate faster than conventional classification-based tracking methods.
Siamese Cascaded Region Proposal Networks for Real-Time Visual Tracking
C-RPN is trained end-to-end with the multi-task loss function.
Real-Time Visual Tracking and Identification for a Team of Homogeneous Humanoid Robots
The use of a team of humanoid robots to collaborate in completing a task is an increasingly important field of research.
FPGA-based Acceleration System for Visual Tracking
In order to improve the tracking speed and reduce the overall power consumption of visual tracking, this paper proposes a real-time visual tracking algorithm based on DSST(Discriminative Scale Space Tracking) approach.
Structured Siamese Network for Real-Time Visual Tracking
In this paper, we circumvent this issue by proposing a local structure learning method, which simultaneously considers the local patterns of the target and their structural relationships for more accurate target tracking.
Deep Meta Learning for Real-Time Target-Aware Visual Tracking
In this paper, we propose a novel on-line visual tracking framework based on the Siamese matching network and meta-learner network, which run at real-time speeds.
UCT: Learning Unified Convolutional Networks for Real-time Visual Tracking
Convolutional neural networks (CNN) based tracking approaches have shown favorable performance in recent benchmarks.
Real-Time Visual Tracking: Promoting the Robustness of Correlation Filter Learning
By exploiting the anisotropy of the filter response, three sparsity related loss functions are proposed to alleviate the overfitting issue of previous methods and improve the overall tracking performance.
