Hock Soon Seah
Nanyang Technological University, Harbin Institute of Technology
Papers
5
Total Citations
63
H-Index
4
About
Hock Soon Seah is a leading researcher in robotics and artificial intelligence, specializing in 3D scene perception, visual semantic navigation, and robot environmental perception for indoor service robots. His major contributions center on developing advanced deep learning and multi-sensor fusion techniques to enable robots to autonomously understand and interact with cluttered indoor environments. Notably, his work on "Multi-View Fusion-Based 3D Object Detection for Robot Indoor Scene Perception" (28 citations) addresses the critical challenge of incomplete object observation, while his "Multi-Channel Convolutional Neural Network Based 3D Object Detection" (24 citations) advances semantic environmental understanding beyond basic geometric reconstruction. Seah also pioneered the "Object-Aware Hybrid Map" for visual semantic navigation, integrating object-level semantics with metric maps to facilitate intuitive human-robot interaction. His research on CNN-based visual relocalization further enhances robot localization robustness. With a cumulative impact of over 60 citations across his most-cited works, Seah’s innovations are foundational for creating perceptive, autonomous service robots capable of long-term operation in complex indoor settings.
Research Focus
Key Achievements
Top Papers
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- 3Object-Aware Hybrid Map for Indoor Robot Visual Semantic Navigation5 citations · 2019
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