A Reinforcement Learning Approach for Sequential Spatial Transformer Networks. - Fatemeh Azimi; Federico Raue; Jörn Hees; Andreas Dengel 001 (ICANN (1), 2019)

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 001 (ICPR, 2020)

Hybrid Sequence to Sequence Model for Video Object Segmentation. - Fatemeh Azimi; Stanislav Frolov; Federico Raue; Jörn Hees; Andreas Dengel 001 (CoRR, 2020)

Rethinking RNN-Based Video Object Segmentation. - Fatemeh Azimi; Federico Raue; Jörn Hees; Andreas Dengel 001 (VISIGRAPP (Revised Selected Papers), 2021)

Hybrid-S2S: Video Object Segmentation with Recurrent Networks and Correspondence Matching. - Fatemeh Azimi; Stanislav Frolov; Federico Raue; Jörn Hees; Andreas Dengel 001 (VISIGRAPP (4: VISAPP), 2021)

Spatial Transformer Networks for Curriculum Learning. - Fatemeh Azimi; Jean-Francois Jacques Nicolas Nies; Sebastian Palacio; Federico Raue; Jörn Hees; Andreas Dengel 001 (CoRR, 2021)

Self-supervised Test-time Adaptation on Video Data. - Fatemeh Azimi; Sebastian Palacio; Federico Raue; Jörn Hees; Luca Bertinetto; Andreas Dengel 001 (WACV, 2022)

Sequential Spatial Transformer Networks for Salient Object Classification. - David Dembinsky; Fatemeh Azimi; Federico Raue; Jörn Hees; Sebastian Palacio; Andreas Dengel 001 (ICPRAM, 2023)

S3Track: Self-supervised Tracking with Soft Assignment Flow. - Fatemeh Azimi; Fahim Mannan; Felix Heide (CoRR, 2023)

Automated Crop Residue Estimation via Unsupervised Techniques Using High-Resolution UAS RGB Imagery. - Fatemeh Azimi; Jinha Jung (Remote. Sens., 2024)

Towards Image and Video Understanding in Challenging Scenarios. - Fatemeh Azimi (2025)