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Bridge3D: Enabling Vision-Language-Action Models to See and Act in 3D
Vision-Language-Action (VLA) models have demonstrated remarkable generalization in robotic manipulation via large-scale multimodal pretraining. However, VLA models are mainly trained on 2D-centric observations, which inherently constrains their capacity for precise spatial manipulation. Previous methods enhance 3D awareness by introducing implicit spatial priors, but still lack explicit geometry guidance. In this paper, we propose Bridge3D that integrates both implicit and explicit 3D geometry guidance into pre-trained 2D VLA models, enabling them to ''see'' and ''act'' in 3D. Bridge3D introdu
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-21T12:59:57.000Z
First collected: 2026-09-23T08:01:43.213Z. This is not the publication date.