Search Results for author:
Found 3 papers, 1 papers with code
Deep Convolutional Correlation Iterative Particle Filter for Visual Tracking
This work proposes a novel framework for visual tracking based on the integration of an iterative particle filter, a deep convolutional neural network, and a correlation filter.
Unsupervised Spatio-temporal Latent Feature Clustering for Multiple-object Tracking and Segmentation
The feature vectors and the constraints graphs are then provided to the kmeans clustering algorithm to separate the corresponding data points in the latent space.
Deep Convolutional Likelihood Particle Filter for Visual Tracking
We propose a novel particle filter for convolutional-correlation visual trackers.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
