pith:HS5S2APJ
Spatial-MLLM: Boosting MLLM Capabilities in Visual-based Spatial Intelligence
Spatial-MLLM equips multimodal language models with stronger 3D spatial reasoning using only 2D image and video inputs.
arxiv:2505.23747 v1 · 2025-05-29 · cs.CV · cs.AI · cs.LG
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Claims
our spatial-MLLM achieves state-of-the-art performance in a wide range of visual-based spatial understanding and reasoning tasks
that initializing a spatial encoder from the backbone of a feed-forward visual geometry foundation model will reliably extract usable 3D structure features from purely 2D image or video inputs without any 3D supervision
Spatial-MLLM boosts MLLM spatial intelligence from 2D inputs via dual encoders initialized from geometry models plus space-aware sampling, claiming state-of-the-art results.
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| First computed | 2026-05-17T23:38:48.490187Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
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| Schema | pith-number/v1.0 |
Canonical hash
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# expect: 3cbb2d01e92142fc93ae34c7d780a6b5155da6d2bc87b6c8db06e493bb4d329c
Canonical record JSON
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