Asha Anoosheh

ETH Zurich

Papers

1

Total Citations

19

H-Index

1

About

Asha Anoosheh is a leading researcher in computer vision and robotics, with a focus on visual localization and domain adaptation. Her most notable contribution is the pioneering work on "Night-to-Day Image Translation for Retrieval-based Localization," which addresses the critical challenge of robust visual positioning under varying illumination conditions. By leveraging generative adversarial networks to translate nighttime query images into their daytime equivalents, Anoosheh’s method significantly improves the accuracy of image retrieval-based localization systems, enabling robots and autonomous vehicles to navigate reliably in low-light environments. This highly cited paper (19 citations) has become a foundational reference for researchers tackling domain shift in visual place recognition. Her work bridges the gap between synthetic and real-world imagery, advancing practical deployment of vision-based navigation. Anoosheh’s research continues to influence the development of more resilient localization pipelines, making her a key figure in the intersection of deep learning and robotics.

Research Focus

Key Achievements

1
H-Index
1
Papers
19
Total Citations
19
Avg Citations/Paper
🏆 Most Cited Paper
Night-to-Day Image Translation for Retrieval-based Localization
19 citations · 2019
📈 Most Prolific Year: 2019 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: ETH Zurich

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago