4RC: 4D Reconstruction via Conditional Querying Anytime and Anywhere
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866913089945862144 |
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| author | Luo, Yihang Zhou, Shangchen Lan, Yushi Pan, Xingang Loy, Chen Change |
| author_facet | Luo, Yihang Zhou, Shangchen Lan, Yushi Pan, Xingang Loy, Chen Change |
| contents | We present 4RC, a unified feed-forward framework for 4D reconstruction from monocular videos. Unlike existing approaches that typically decouple motion from geometry or produce limited 4D attributes such as sparse trajectories or two-view scene flow, 4RC learns a holistic 4D representation that jointly captures dense scene geometry and motion dynamics. At its core, 4RC introduces a novel encode-once, query-anywhere and anytime paradigm: a transformer backbone encodes the entire video into a compact spatio-temporal latent space, from which a conditional decoder can efficiently query 3D geometry and motion for any query frame at any target timestamp. To facilitate learning, we represent per-view 4D attributes in a minimally factorized form by decomposing them into base geometry and time-dependent relative motion. Extensive experiments demonstrate that 4RC outperforms prior and concurrent methods across a wide range of 4D reconstruction tasks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_10094 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | 4RC: 4D Reconstruction via Conditional Querying Anytime and Anywhere Luo, Yihang Zhou, Shangchen Lan, Yushi Pan, Xingang Loy, Chen Change Computer Vision and Pattern Recognition We present 4RC, a unified feed-forward framework for 4D reconstruction from monocular videos. Unlike existing approaches that typically decouple motion from geometry or produce limited 4D attributes such as sparse trajectories or two-view scene flow, 4RC learns a holistic 4D representation that jointly captures dense scene geometry and motion dynamics. At its core, 4RC introduces a novel encode-once, query-anywhere and anytime paradigm: a transformer backbone encodes the entire video into a compact spatio-temporal latent space, from which a conditional decoder can efficiently query 3D geometry and motion for any query frame at any target timestamp. To facilitate learning, we represent per-view 4D attributes in a minimally factorized form by decomposing them into base geometry and time-dependent relative motion. Extensive experiments demonstrate that 4RC outperforms prior and concurrent methods across a wide range of 4D reconstruction tasks. |
| title | 4RC: 4D Reconstruction via Conditional Querying Anytime and Anywhere |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2602.10094 |