摘要
This paper scales object-level reconstruction to complex scenes, advancing interactive scene reconstruction. We introduce two datasets, OmniSim and InterReal, featuring 28 scenes with multiple interactive objects. To tackle the challenge of inaccurate interactive motion recovery in complex scenes, we propose LiveScene, a scene-level language-embedded interactive radiance field that efficiently reconstructs and controls multiple objects. By decomposing the interactive scene into local deformable fields, LiveScene enables separate reconstruction of individual object motions, reducing memory consumption. Additionally, our interaction-aware language embedding localizes individual interactive objects, allowing for arbitrary control using natural language. Our approach demonstrates significant superiority in novel view synthesis, interactive scene control, and language grounding performance through extensive experiments. Project page: https://livescenes.github.io.
| 源语言 | 英语 |
|---|---|
| 期刊 | Advances in Neural Information Processing Systems |
| 卷 | 37 |
| 出版状态 | 已出版 - 2024 |
| 已对外发布 | 是 |
| 活动 | 38th Conference on Neural Information Processing Systems, NeurIPS 2024 - Vancouver, 加拿大 期限: 9 12月 2024 → 15 12月 2024 |
指纹
探究 'LiveScene: Language Embedding Interactive Radiance Fields for Physical Scene Rendering and Control' 的科研主题。它们共同构成独一无二的指纹。引用此
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