Visual Tracking
169 papers with code • 9 benchmarks • 27 datasets
Visual Tracking is an essential and actively researched problem in the field of computer vision with various real-world applications such as robotic services, smart surveillance systems, autonomous driving, and human-computer interaction. It refers to the automatic estimation of the trajectory of an arbitrary target object, usually specified by a bounding box in the first frame, as it moves around in subsequent video frames.
Source: Learning Reinforced Attentional Representation for End-to-End Visual Tracking
Benchmarks
These leaderboards are used to track progress in Visual Tracking
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Libraries
Use these libraries to find Visual Tracking models and implementations
Kinetics
DAVIS
OTB
LaSOT
TrackingNet
OTB-2015
OTB-2013
TNL2K
Kubric
OxUva
Most implemented papers
Tracking Holistic Object Representations
xl-sr/THOR
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The framework leverages the idea of obtaining additional object templates during the tracking process.
GradNet: Gradient-Guided Network for Visual Object Tracking
LPXTT/GradNet-Pytorch
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ICCV 2019
In this work, we propose a novel gradient-guided network to exploit the discriminative information in gradients and update the template in the siamese network through feed-forward and backward operations.
SiamCAR: Siamese Fully Convolutional Classification and Regression for Visual Tracking
ohhhyeahhh/SiamCAR
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CVPR 2020
The proposed framework SiamCAR consists of two simple subnetworks: one Siamese subnetwork for feature extraction and one classification-regression subnetwork for bounding box prediction.
Siamese Box Adaptive Network for Visual Tracking
Most of the existing trackers usually rely on either a multi-scale searching scheme or pre-defined anchor boxes to accurately estimate the scale and aspect ratio of a target.
Probabilistic Regression for Visual Tracking
visionml/pytracking
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CVPR 2020
In this work, we therefore propose a probabilistic regression formulation and apply it to tracking.
High-Performance Long-Term Tracking with Meta-Updater
Most top-ranked long-term trackers adopt the offline-trained Siamese architectures, thus, they cannot benefit from great progress of short-term trackers with online update.
Fully Convolutional Online Tracking
MCG-NJU/FCOT
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To tackle this issue, we present the fully convolutional online tracking framework, coined as FCOT, and focus on enabling online learning for both classification and regression branches by using a target filter based tracking paradigm.
Multi-modal Visual Tracking: Review and Experimental Comparison
Visual object tracking, as a fundamental task in computer vision, has drawn much attention in recent years.
Predictive Visual Tracking: A New Benchmark and Baseline Approach
vision4robotics/LAE-PVT-master
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As a crucial robotic perception capability, visual tracking has been intensively studied recently.
Towards More Flexible and Accurate Object Tracking with Natural Language: Algorithms and Benchmark
wangxiao5791509/Single_Object_Tracking_Paper_List
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CVPR 2021
We believe this benchmark will greatly boost related researches on natural language guided tracking.
