4 citations · 5 across the 2 of their papers we have counts for
5 papers
CHASE: Robust Visual Tracking via Cell-Level Differentiable Neural Architecture Search
Seyed Mojtaba Marvasti-Zadeh, Javad Khaghani, Li Cheng +2
A strong visual object tracker nowadays relies on its well-crafted modules, which typically consist of manually-designed network architectures to deliver high-quality tracking resu…
Adaptive Exploitation of Pre-trained Deep Convolutional Neural Networks for Robust Visual Tracking
Seyed Mojtaba Marvasti-Zadeh, Hossein Ghanei-Yakhdan, Shohreh Kasaei
Due to the automatic feature extraction procedure via multi-layer nonlinear transformations, the deep learning-based visual trackers have recently achieved great success in challen…
COMET: Context-Aware IoU-Guided Network for Small Object Tracking
Seyed Mojtaba Marvasti-Zadeh, Javad Khaghani, Hossein Ghanei-Yakhdan +2
We consider the problem of tracking an unknown small target from aerial videos of medium to high altitudes. This is a challenging problem, which is even more pronounced in unavoida…
Efficient Scale Estimation Methods using Lightweight Deep Convolutional Neural Networks for Visual Tracking
Seyed Mojtaba Marvasti-Zadeh, Hossein Ghanei-Yakhdan, Shohreh Kasaei
In recent years, visual tracking methods that are based on discriminative correlation filters (DCF) have been very promising. However, most of these methods suffer from a lack of r…
Deep Learning for Visual Tracking: A Comprehensive Survey
Seyed Mojtaba Marvasti-Zadeh, Li Cheng, Hossein Ghanei-Yakhdan +1
Visual target tracking is one of the most sought-after yet challenging research topics in computer vision. Given the ill-posed nature of the problem and its popularity in a broad r…