LiveScene: Language Embedding Interactive Radiance Fields for Physical Scene Rendering and Control

Delin Qu, Qizhi Chen, Pingrui Zhang, Xianqiang Gao, Bin Zhao, Zhigang Wang, Dong Wang, Xuelong Li

Research output: Contribution to journalConference articlepeer-review

Abstract

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.

Original languageEnglish
JournalAdvances in Neural Information Processing Systems
Volume37
StatePublished - 2024
Externally publishedYes
Event38th Conference on Neural Information Processing Systems, NeurIPS 2024 - Vancouver, Canada
Duration: 9 Dec 202415 Dec 2024

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