The authors release the 3DVQL benchmark for 3D multimodal visual query localization and show that a lift-and-attention fusion module outperforms prior fusion baselines on it.
Scannet: Richly-annotated 3d reconstructions of indoor scenes
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POMA-3D learns self-supervised 3D scene representations from point maps and improves performance on geometric 3D tasks including navigation and scene retrieval.
KFC-W is a self-supervised 3D-aware video model trained on videos and multiview internet photos that produces geometrically consistent interpolations between unposed input images without any 3D annotations.
citing papers explorer
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Towards Visual Query Localization in the 3D World
The authors release the 3DVQL benchmark for 3D multimodal visual query localization and show that a lift-and-attention fusion module outperforms prior fusion baselines on it.
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POMA-3D: The Point Map Way to 3D Scene Understanding
POMA-3D learns self-supervised 3D scene representations from point maps and improves performance on geometric 3D tasks including navigation and scene retrieval.
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KFC-W: Generating 3D-Consistent Videos from Unposed Internet Photos
KFC-W is a self-supervised 3D-aware video model trained on videos and multiview internet photos that produces geometrically consistent interpolations between unposed input images without any 3D annotations.