Investigating vision transformers for bridging domain gap in satellite pose estimation
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Lotti et al.'s lightweight architecture shows an increase of 273% in inference speed with only nominal performance degradation.
“The results from the paper show an increase of 273% in the inference speed with only nominal performance degradation.”
From A survey on deep learning-based monocular spacecraft pose estimation: Current state, limitations and prospects (2023) · cites this paper as [58]
Lotti et al. showed that using Transformer-based architectures combined with adversarial learning can further mitigate the domain gap problem in spacecraft pose estimation algorithms.
“Recently Lotti et al. [58] showed that using Transformer-based [39] architectures combined with adversarial learning can further mitigate the domain gap problem in spacecraft pose estimation algorithms.”
From A survey on deep learning-based monocular spacecraft pose estimation: Current state, limitations and prospects (2023) · cites this paper as [58]
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Deep Learning for Spacecraft Pose Estimation from Photorealistic Rendering
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Pauly, L., Rharbaoui, W., Shneider, C., Rathinam, A., Gaudillière, V., & Aouada, D. (2023) · Acta Astronautica · doi:10.1016/j.actaastro.2023.08.001 · Cited by 121 · see citing works
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Satellite Pose Set Estimation by Uncertainty-Guided Conformal Keypoint Detection
Wang, J., Li, Z., Sun, C., Guo, Y., Wang, Z., & Yu, Q. (2025) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2025.3598481 · Cited by 3 · see citing works
Adaptive Granularity-Fused Keypoint Detection for 6D Pose Estimation of Space Targets
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Self-citationEvent‐Based Attitude‐Driven Functional Damage Assessment of Space Targets
Lei, X., Tan, Y., & Zhu, L. (2026) · IET Image Processing · doi:10.1049/ipr2.70480
Diaconu, C., Bompani, L., Dequino, A., Nadalini, D., & Conti, F. (2026) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn69854.2026.11729795
- Authors
- Lotti, A., Modenini, D., & Tortora, P.
- Affiliations
- University of Bologna (IT)
- Corresponding author
- Lotti, Alessandro
- Venue
- Studies in Computational Intelligence
- Publisher
- Springer Nature Switzerland
- Published
- 2023
- Pages
- 299-314
- ISSN
- 1860-949X (ISSN-L)
- 1860-9503
- OpenAlex
- W4380899229
- Cited by
- 7
- References
- 21
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 1 · 2023: 1
- FWCI
- 3.57
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- Locations
- Studies in computational intelligence (publishedVersion)
- Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › Space Satellite Systems and Control
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Domain Adaptation and Few-Shot Learning
- Keywords
- satellite pose estimation, vision transformer, Swin Transformer, domain gap, domain shift, adversarial domain adaptation, lightweight neural networks, data augmentation
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