Video Object Tracking
28 papers with code • 3 benchmarks • 11 datasets
Video Object Detection aims to detect targets in videos using both spatial and temporal information. It's usually deeply integrated with tasks such as Object Detection and Object Tracking.
Benchmarks
These leaderboards are used to track progress in Video Object Tracking
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Libraries
Use these libraries to find Video Object Tracking models and implementations
GOT-10k
CATER
SoccerNet-v2
VOT2014
BL30K
TREK-150
VideoCube
RF100
SOTVerse
Latest papers with no code
Improving Human Annotation in Single Object Tracking
We then use different techniques to smooth the trajectories at certain degree.
A Comparison of CNN and Classic Features for Image Retrieval
Many methods use image gradients in different stages of the detection-description pipeline to describe local image structures.
DAWN: Dual Augmented Memory Network for Unsupervised Video Object Tracking
Our Dual Augmented Memory Network (DAWN) is unique in remembering both target and background, and using an improved attention LSTM memory to guide the focus on memorized features.
Unsupervised learning-based long-term superpixel tracking
Finding correspondences between structural entities decomposing images is of high interest for computer vision applications.
Deep Siamese Networks with Bayesian non-Parametrics for Video Object Tracking
We present a novel algorithm utilizing a deep Siamese neural network as a general object similarity function in combination with a Bayesian optimization (BO) framework to encode spatio-temporal information for efficient object tracking in video.
Depth-Adaptive Computational Policies for Efficient Visual Tracking
Current convolutional neural networks algorithms for video object tracking spend the same amount of computation for each object and video frame.
MAVOT: Memory-Augmented Video Object Tracking
We introduce a one-shot learning approach for video object tracking.
Robust video object tracking via Bayesian model averaging based feature fusion
In this article, we are concerned with tracking an object of interest in video stream.
Robust video object tracking using particle filter with likelihood based feature fusion and adaptive template updating
In this solution, the bootstrap particle filter (PF) is initialized by an object detector, which models the time-evolving background of the video signal by an adaptive Gaussian mixture.
Automatic tracking of protein vesicles
In this thesis, we formulate such tracking problem as video object tracking problem, and design a dynamic programming method for tracking single object.
