GHOST: Grounded Human Motion Generation with Open Vocabulary Scene-and-Text Contexts

Understand

The connection between our 3D surroundings and the descriptive language that characterizes them would be well-suited for localizing and generating human motion in context but for one problem.

• The complexity introduced by multiple modalities makes capturing this connection challenging with a fixed set of descriptors.
• Specifically, closed vocabulary scene encoders, which require learning text-scene associations from scratch, have been favored in the literature, often resulting in inaccurate motion grounding.
• In this paper, we propose a method that integrates an open vocabulary scene encoder into the architecture, establishing a robust connection between text and scene.