Qwen-3D: Enhancing Spatial Reasoning via Multi-View Geometric Cues
udmrzn · x · 2026-08-07
Qwen-3D is a generalist 3D vision-language model designed for comprehensive spatial understanding. It leverages depth and camera poses to fuse multi-view inputs into a shared 3D space, providing a natural compression mechanism for visual streams.
- Core Architecture: Introduces 3D Rotary Positional Embeddings (3D RoPE) and a dense mask decoder. This allows attention mechanisms to operate directly in 3D scene space rather than independent image frames, overcoming the limitations of frame-centric tokenization.
- Supported Tasks: Capably handles spatial reasoning, 3D grounding, segmentation, and visual question answering (VQA).
- Performance: Outperforms prior 3D Large Multimodal Models on various tasks while fully retaining its original 2D capabilities.
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