Eshed Ohn-Bar* — accepted AI-conference papers

2024

Neural Volumetric World Models for Autonomous Driving

Zanming Huang*, Jimuyang Zhang*, Eshed Ohn-Bar*

ECCV 2024poster

"Effectively navigating a dynamic 3D world requires a comprehensive understanding of the 3D geometry and motion of surrounding objects and layouts. However, existing methods for perception and planning in autonomous driving primarily rely on a 2D spatial representation, based on a bird’s eye perspec…

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2024

Unified Local-Cloud Decision-Making via Reinforcement Learning

Kathakoli Sengupta, Zhongkai Shangguan, Sandesh Bharadwaj, Sanjay Arora, Eshed Ohn-Bar*, Renato Mancuso

ECCV 2024poster

"Embodied vision-based real-world systems, such as mobile robots, require a careful balance between energy consumption, compute latency, and safety constraints to optimize operation across dynamic tasks and contexts. As local computation tends to be restricted, offloading the computation, , to a rem…

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