Qwen-3D: A Generalist 3D Vision-Language Model for Spatial Understanding

arXiv:2608.02980 · cs.CV · Submitted 2026-08-04 · Read on arXiv

cs.CV

Submitted: 2026-08-04

Updated: 2026-10-13

Project page: https://qwen-3d.github.io

Terminology

• Grounding — 3× in this paper · explained in 3 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Instance Segmentation — 1× in this paper · explained in 3 episodes
• Temporal Reasoning — 1× in this paper · explained in 2 episodes
• Tokenization — 1× in this paper · explained in 2 episodes

Sources

• Matterport3D: Learning from RGB-D Data in Indoor Environments
• Grounded 3D-LLM with Referent Tokens
• Scene-LLM: Extending Language Model for 3D Visual Understanding and Reasoning
• An Embodied Generalist Agent in 3D World
• SQA3D: Situated Question Answering in 3D Scenes
• MoGe: Unlocking Accurate Monocular Geometry Estimation for Open-Domain Images with Optimal Training Supervision
• Qwen2.5 Technical Report
• Learning from Videos for 3D World: Enhancing MLLMs with 3D Vision Geometry Priors
• Unifying 3D Vision-Language Understanding via Promptable Queries

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