LLMI3D introduces a novel approach enabling Multimodal Large Language Models to accurately perceive 3D structure from single 2D images, addressing key limitations in current methods.

• Creates a unified framework combining spatial feature extraction with LLM reasoning
• Employs specialized prompting techniques to improve geometric understanding
• Achieves superior performance in open-world 3D perception tasks
• Enables zero-shot generalization across diverse real-world scenarios

This research significantly advances engineering capabilities in autonomous driving, robotics, and AR/VR applications by bridging the gap between 2D vision and 3D understanding without specialized models.

LLMI3D: MLLM-based 3D Perception from a Single 2D Image