Maryam Babaee

Orcid: 0000-0003-0887-8988

According to our database1, Maryam Babaee authored at least 14 papers between 2016 and 2021.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2021
Multiple People Tracking and Gait Recognition for Video Surveillance.
PhD thesis, 2021

2019
A dual CNN-RNN for multiple people tracking.
Neurocomputing, 2019

Person identification from partial gait cycle using fully convolutional neural networks.
Neurocomputing, 2019

Convolutional Neural Networks with Layer Reuse.
Proceedings of the 2019 IEEE International Conference on Image Processing, 2019

Outlier-Robust Neural Aggregation Network for Video Face Identification.
Proceedings of the 2019 IEEE International Conference on Image Processing, 2019

Gait Energy Image Restoration Using Generative Adversarial Networks.
Proceedings of the 2019 IEEE International Conference on Image Processing, 2019

2018
Multiple People Tracking Using Hierarchical Deep Tracklet Re-identification.
CoRR, 2018

Person Identification from Partial Gait Cycle Using Fully Convolutional Neural Network.
CoRR, 2018

Occlusion Handling in Tracking Multiple People Using RNN.
Proceedings of the 2018 IEEE International Conference on Image Processing, 2018

Gait Recognition from Incomplete Gait Cycle.
Proceedings of the 2018 IEEE International Conference on Image Processing, 2018

Gait Energy Image Reconstruction from Degraded Gait Cycle Using Deep Learning.
Proceedings of the Computer Vision - ECCV 2018 Workshops, 2018

2017
Joint tracking and gait recognition of multiple people in video.
Proceedings of the 2017 IEEE International Conference on Image Processing, 2017

View-Invariant Gait Representation Using Joint Bayesian Regularized Non-negative Matrix Factorization.
Proceedings of the 2017 IEEE International Conference on Computer Vision Workshops, 2017

2016
Discriminative Nonnegative Matrix Factorization for dimensionality reduction.
Neurocomputing, 2016


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