Visual Object Tracking
150 papers with code • 21 benchmarks • 26 datasets
Visual Object Tracking is an important research topic in computer vision, image understanding and pattern recognition. Given the initial state (centre location and scale) of a target in the first frame of a video sequence, the aim of Visual Object Tracking is to automatically obtain the states of the object in the subsequent video frames.
Benchmarks
These leaderboards are used to track progress in Visual Object Tracking
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Libraries
Use these libraries to find Visual Object Tracking models and implementations
OTB
LaSOT
GOT-10k
TrackingNet
YouTube-VOS 2018
OTB-2015
VOT2018
VOT2016
OTB-2013
VOT2017
Latest papers with no code
RTrack: Accelerating Convergence for Visual Object Tracking via Pseudo-Boxes Exploration
Single object tracking (SOT) heavily relies on the representation of the target object as a bounding box.
BASE: Probably a Better Approach to Multi-Object Tracking
The field of visual object tracking is dominated by methods that combine simple tracking algorithms and ad hoc schemes.
Leveraging the Power of Data Augmentation for Transformer-based Tracking
Due to long-distance correlation and powerful pretrained models, transformer-based methods have initiated a breakthrough in visual object tracking performance.
Efficient Training for Visual Tracking with Deformable Transformer
Recent Transformer-based visual tracking models have showcased superior performance.
Towards Efficient Training with Negative Samples in Visual Tracking
This study introduces a more efficient training strategy to mitigate overfitting and reduce computational requirements.
BackTrack: Robust template update via Backward Tracking of candidate template
An effective method to tackle these challenges is template update, which updates the template to reflect the change of appearance in the target object during tracking.
Learning Spatial Distribution of Long-Term Trackers Scores
Long-Term tracking is a hot topic in Computer Vision.
Heteroskedastic Geospatial Tracking with Distributed Camera Networks
Visual object tracking has seen significant progress in recent years.
Tracking by 3D Model Estimation of Unknown Objects in Videos
We argue that this representation is limited and instead propose to guide and improve 2D tracking with an explicit object representation, namely the textured 3D shape and 6DoF pose in each video frame.
SiamTHN: Siamese Target Highlight Network for Visual Tracking
The majority of siamese network based trackers now in use treat each channel in the feature maps generated by the backbone network equally, making the similarity response map sensitive to background influence and hence challenging to focus on the target region.
