May 18, 2021 · In this paper, we make several improvements aimed at tackling uncertainty and improving robustness in object tracking.
Visual tracking aims to estimate the trajectory of a target in a video sequence. It has wide applications ranging from human motion analysis, human-computer ...
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How to model uncertainty?
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In this paper, specifically for uncertainties defined on images, we show how revisiting results from Random Field theory (RFT) when paired with DNN tools.
This paper extends iterative alignment in the domain of 2D similarity transformations so that it represents the uncertainty in the position of each model ...
Model Uncertainty Guides Visual Object Tracking, Lijun Zhou, Antoine Ledent ... "Visual Object Tracking for Unmanned Aerial Vehicles: A Benchmark and New Motion ...
In this paper, we propose a novel data uncertainty guided multi-phase learning method for semi-supervised object de- tection. The multi-phase training method ...
"Model Uncertainty Guides Visual Object Tracking." AAAI (2021). [paper]. UPA ... "Visual Object Tracking for Unmanned Aerial Vehicles: A Benchmark and New Motion ...
One of the most challenging problems in autonomous driving, and in com- puter vision in general, is the task of object detection. Recently, the advances.
In the following sections, we will review how the previous work learns a probability distribution and propose an alter- native approach. A. Learning Uncertainty.
A single position-tracking mechanism could account for both spatial and temporal patterns, providing a unified computational explanation.