Author

Hideo Saito

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Preprint Oct 2026

EgoReveal: Learning Active Vision and Object Manipulation under Partial Occlusions from Egocentric Demonstrations

Learning from Demonstrations (LfD) enables robots to learn object manipulation directly from human demonstrations. In contrast to resource-intensive and labor-intensive teleoperation, egocentric demonstrations are easy to collect, enabling scalable data collection. Manipulated objects are often partially occluded in ev...

Hiromu Kurihara, Kazutoshi Tanaka, Masashi Hatano et al. · 0 citations

#machine learning Preprint Sep 2026

EgoNeMo: Transferable Map of Pedestrian Dynamics via Egocentric LiDAR Scan

This paper proposes a transferable Map of Dynamics (MoD) framework that generalizes to unknown environments using only egocentric 3D LiDAR point clouds to overcome the long-standing limitation of traditional MoD methods. While MoDs are essential for encoding human motion characteristics to enable accurate pedestrian tr...

Azusa Sawada, Allan Wang, Hideo Saito et al. · 0 citations