PlaceIt3D: Language-Guided Object Placement in Real 3D Scenes
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Abstract (arXiv)
We introduce the novel task of Language-Guided Object Placement in Real 3D Scenes. Our model is given a 3D scene's point cloud, a 3D asset, and a textual prompt broadly describing where the 3D asset should be placed. The task here is to find a valid placement for the 3D asset that respects the prompt. Compared with other language-guided localization tasks in 3D scenes such as grounding, this task has specific challenges: it is ambiguous because it has multiple valid solutions, and it requires reasoning about 3D geometric relationships and free space. We inaugurate this task by proposing a new benchmark and evaluation protocol. We also introduce a new dataset for training 3D LLMs on this task, as well as the first method to serve as a non-trivial baseline. We believe that this challenging task and our new benchmark could become part of the suite of benchmarks used to evaluate and compare generalist 3D LLM models.
Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 48 of its 63 references that are in the map. First posted on arXiv 8 May 2025.
Builds on
48 of 63 references.
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36 more
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Built on by
Citing papers per year: 2026: 9.
9 papers.
- 2026PhyScensis: Physics-Augmented LLM Agents for Complex Physical Scene Arrangementcited by 7
- 20263D-Layout-R1: Structured Reasoning for Language-Instructed Spatial Editingcited by 4
- 2026Lucida: Parse, Generate, and Place for Composable Real-to-Sim Scene Modelingcited by 2
- 2026SpatialAct: Probing Spatial Reasoning-to-Action Capabilities of VLM Agents in 3D Scenescited by 1
- 2026Beyond Single Object: Learning 3D Relations with Large Language Modelscited by 1
- 2026HiddenObjects: Scalable Diffusion-Distilled Spatial Priors for Object Placementcited by 0
- 2026ReRef-3D: A Benchmark for Spatial Referring Expression-Guided 3D Scene Rearrangementcited by 0
- 2026SPHERE: Adaptive VR Indoor Scene Generation via LLM-Enhanced Spatial Preference Learning and Human-in-the-Loop RLcited by 0
- 2026Mind the Spatial Gap: A Benchmark for Geospatial Reasoning and Constrained Spatial Editingcited by 0
- 2026Mind the Spatial Gap: A Benchmark for Geospatial Reasoning and Constrained Spatial Editing9 Oct 2026
- 2026SPHERE: Adaptive VR Indoor Scene Generation via LLM-Enhanced Spatial Preference Learning and Human-in-the-Loop RL1 Oct 2026
- 2026Lucida: Parse, Generate, and Place for Composable Real-to-Sim Scene Modeling31 Aug 2026
- 2026ReRef-3D: A Benchmark for Spatial Referring Expression-Guided 3D Scene Rearrangement17 Aug 2026
- 2026Beyond Single Object: Learning 3D Relations with Large Language Models16 Aug 2026
- 2026SpatialAct: Probing Spatial Reasoning-to-Action Capabilities of VLM Agents in 3D Scenes29 May 2026
- 2026HiddenObjects: Scalable Diffusion-Distilled Spatial Priors for Object Placement12 Apr 2026
- 20263D-Layout-R1: Structured Reasoning for Language-Instructed Spatial Editing23 Mar 2026
- 2026PhyScensis: Physics-Augmented LLM Agents for Complex Physical Scene Arrangement16 Feb 2026