Fatemeh Azimi

According to our database, Fatemeh Azimi authored at least 11 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Towards Image and Video Understanding in Challenging Scenarios.

Fatemeh Azimi

PhD thesis, 2025

2024

Automated Crop Residue Estimation via Unsupervised Techniques Using High-Resolution UAS RGB Imagery.

Fatemeh Azimi, Jinha Jung

Remote. Sens., April, 2024

2023

S³Track: Self-supervised Tracking with Soft Assignment Flow.

Fatemeh Azimi, Fahim Mannan, Felix Heide

CoRR, 2023

Sequential Spatial Transformer Networks for Salient Object Classification.

David Dembinsky, Fatemeh Azimi, Federico Raue, Jörn Hees, Sebastian Palacio, Andreas Dengel

Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods, 2023

2022

Self-supervised Test-time Adaptation on Video Data.

Fatemeh Azimi, Sebastian Palacio, Federico Raue, Jörn Hees, Luca Bertinetto, Andreas Dengel

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

2021

Spatial Transformer Networks for Curriculum Learning.

Fatemeh Azimi, Jean-Francois Jacques Nicolas Nies, Sebastian Palacio, Federico Raue, Jörn Hees, Andreas Dengel

CoRR, 2021

Hybrid-S2S: Video Object Segmentation with Recurrent Networks and Correspondence Matching.

Fatemeh Azimi, Stanislav Frolov, Federico Raue, Jörn Hees, Andreas Dengel

Proceedings of the 16th International Joint Conference on Computer Vision, 2021

Rethinking RNN-Based Video Object Segmentation.

Fatemeh Azimi, Federico Raue, Jörn Hees, Andreas Dengel

Proceedings of the Computer Vision, Imaging and Computer Graphics Theory and Applications, 2021

2020

Hybrid Sequence to Sequence Model for Video Object Segmentation.

Fatemeh Azimi, Stanislav Frolov, Federico Raue, Jörn Hees, Andreas Dengel

CoRR, 2020

Revisiting Sequence-to-Sequence Video Object Segmentation with Multi-Task Loss and Skip-Memory.

Fatemeh Azimi, Benjamin Bischke, Sebastian Palacio, Federico Raue, Jörn Hees, Andreas Dengel

Proceedings of the 25th International Conference on Pattern Recognition, 2020

2019

A Reinforcement Learning Approach for Sequential Spatial Transformer Networks.

Fatemeh Azimi, Federico Raue, Jörn Hees, Andreas Dengel

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Theoretical Neural Computation, 2019