Emily Steiner — accepted AI-conference papers

2026

ReScene4D: Temporally Consistent Semantic Instance Segmentation of Evolving Indoor 3D Scenes

Emily Steiner, Jianhao Zheng, Henry Howard-Jenkins, Chris Xie, Iro Armeni

CVPR 2026

Indoor environments evolve as objects move, appear, or leave the scene. Capturing these dynamics requires maintaining temporally consistent instance identities across intermittently captured 3D scans, even when changes are unobserved. We introduce and formalize the task of temporally sparse 4D indoo

Cited by 0 Source ↗Scholar ↗

2025

Accelerating Real-World Overtaking in F1TENTH Racing Employing Reinforcement Learning Methods

Emily Steiner, Daniel van der Spuy, Futian Zhou, Afereti Pama, Minas Liarokapis, Henry Williams

IROS 2025

While autonomous racing performance in Time-Trial scenarios has seen significant progress and development, autonomous wheel-to-wheel racing and overtaking are still severely limited. These limitations are particularly apparent in real-life driving scenarios where state-of-the-art algorithms struggle

Cited by 1 Source ↗Scholar ↗