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arxiv:2512.12768

CoRe3D: Collaborative Reasoning as a Foundation for 3D Intelligence

Published on Dec 14
· Submitted by
Ismini Lourentzou
on Dec 16
Authors:
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Abstract

A reasoning framework for 3D understanding and generation, CoRe3D, uses spatially grounded reasoning to align high-level language intent with low-level 3D content, ensuring local consistency and alignment with descriptions.

AI-generated summary

Recent advances in large multimodal models suggest that explicit reasoning mechanisms play a critical role in improving model reliability, interpretability, and cross-modal alignment. While such reasoning-centric approaches have been proven effective in language and vision tasks, their extension to 3D remains underdeveloped. CoRe3D introduces a unified 3D understanding and generation reasoning framework that jointly operates over semantic and spatial abstractions, enabling high-level intent inferred from language to directly guide low-level 3D content formation. Central to this design is a spatially grounded reasoning representation that decomposes 3D latent space into localized regions, allowing the model to reason over geometry in a compositional and procedural manner. By tightly coupling semantic chain-of-thought inference with structured spatial reasoning, CoRe3D produces 3D outputs that exhibit strong local consistency and faithful alignment with linguistic descriptions.

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Paper submitter
edited 8 days ago

A dual semantic + geometric reasoning framework with octant-based 3D tokens and multi-critic GRPO, achieving SoTA on text-to-3D, image-to-3D, and 3D captioning.

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