Nov 5, 2018 · This paper presents a deep network-based direction tracker. A three-layer convolutional neural network is used to extract the object feature, ...
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[PDF] Deep Directional Network for Object Tracking | Semantic Scholar
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This work proposes a target direction classification network based on CNNs that has a directional shortcut to the tracking target, unlike the particle ...
Jul 28, 2020 · In this paper, a new efficient DOA estimation approach based on the deep neural networks (DNN) is proposed, in which a nonlinear mapping that relates the ...
Jul 10, 2024 · This paper presents a novel deep learning-based method that integrates radar and camera data to enhance the accuracy and robustness of Multi-Object Tracking in ...
Feb 16, 2023 · In this paper, we tackle the problem of event-based object tracking by a novel architecture with a discriminatively trained SNN, called the Spiking ...
Apr 26, 2020 · Object tracking means estimating the state of the target object present in the scene from previous information.
In our research, we focus on the creation of neural networks for multi-object pose estimation from rgb images.
Nov 1, 2023 · I'm new to NNs but if I were doing this I would develop features using transformers for object velocity (movement direction and speed/accel ...
The ADNet is designed to generate actions to find the location and the size of the target object in a new frame. The ADNet learns the policy that selects the ...
Oct 28, 2018 · In this paper, we harness the power of deep learning for data association in tracking by jointly modelling object appearances and their affinities between ...
Missing: Directional | Show results with:Directional