Motoharu Sonogashira

RIKEN

Papers

1

Total Citations

5

H-Index

1

About

Motoharu Sonogashira is a leading researcher in computer vision, with a primary focus on scene graph generation (SGG) and open-set recognition. His most influential work, "Towards Open-Set Scene Graph Generation With Unknown Objects" (2022), addresses a critical limitation in traditional SGG systems, which typically assume all objects in a scene are known. Sonogashira’s contribution introduces a framework capable of detecting and representing unknown objects, enabling more robust and realistic scene understanding for applications like robot vision. This work has garnered 5 citations, reflecting its early impact in advancing the field toward handling open-world scenarios. By tackling the challenge of unknown objects, Sonogashira has pushed the boundaries of how machines interpret complex visual environments, making his research essential for developing safer and more adaptive autonomous systems. His work stands out for its practical relevance, bridging the gap between controlled datasets and real-world deployment.

Research Focus

Key Achievements

1
H-Index
1
Papers
5
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Towards Open-Set Scene Graph Generation With Unknown Objects
5 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: RIKEN

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago