Article

EnerVerse-AC: Envisioning Embodied Environments with Action Condition

2025-05-15

Abstract excerpt

Robotic imitation learning has advanced from solving static tasks to addressing dynamic interaction scenarios, but testing and evaluation remain costly and challenging due to the need for real-time interaction with dynamic environments. We propose EnerVerse-AC (EVAC), an action-conditional world model that generates future visual observations based on an agent's predicted actions, enabling realistic and controllab...

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Literature Corpus work: e19d3f26-46e2-50cd-86b4-d9b8964a854a
DOI: 10.20944/preprints202505.1193.v1

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