3EED: Ground Everything Everywhere in 3D
Not on the map. Why?
Abstract (arXiv)
Visual grounding in 3D is the key for embodied agents to localize language-referred objects in open-world environments. However, existing benchmarks are limited to indoor focus, single-platform constraints, and small scale. We introduce 3EED, a multi-platform, multi-modal 3D grounding benchmark featuring RGB and LiDAR data from vehicle, drone, and quadruped platforms. We provide over 128,000 objects and 22,000 validated referring expressions across diverse outdoor scenes -- 10x larger than existing datasets. We develop a scalable annotation pipeline combining vision-language model prompting with human verification to ensure high-quality spatial grounding. To support cross-platform learning, we propose platform-aware normalization and cross-modal alignment techniques, and establish benchmark protocols for in-domain and cross-platform evaluations. Our findings reveal significant performance gaps, highlighting the challenges and opportunities of generalizable 3D grounding. The 3EED dataset and benchmark toolkit are released to advance future research in language-driven 3D embodied perception.
Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 90 of its 108 references that are in the map. First posted on arXiv 3 Nov 2025.
Builds on
90 of 108 references.
References · 90
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38 more
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50 most cited of 90 All 90 (JSON)
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Citing papers per year: 2025: 2; 2026: 10.
12 papers.
- 2025Vision-Language-Action Models for Autonomous Driving: Past, Present, and Futurecited by 33
- 2026WildDet3D: Scaling Promptable 3D Detection in the Wildcited by 14
- 2025U4D: Uncertainty-Aware 4D World Modeling from LiDAR Sequencescited by 7
- 2026Qwen-3D: A Generalist 3D Vision-Language Model for Spatial Understandingcited by 5
- 2026AdaSFormer: Adaptive Serialized Transformers for Monocular Semantic Scene Completion from Indoor Environmentscited by 3
- 2026OmniLiDAR: A Unified Diffusion Framework for Multi-Domain 3D LiDAR Generationcited by 2
- 2026EventDrive: Event Cameras for Vision-Language Driving Intelligencecited by 2
- 2026CitySTAR: Structured and Topology-Aware Reasoning for Open-Vocabulary Urban 3D Groundingcited by 0
- 2026EmbPASS: Towards Cross-Embodiment Open Panoramic Segmentationcited by 0
- 2026UniMetric: Universal Metric Scale Recovery for Visual Geometry Foundation Modelscited by 0
- 2026Urbex: Agentic Spatial Grounding for City-Scale 3D Scenescited by 0
- 2026VITAL: From Visual Motion to Precise Actioncited by 0
- 2026VITAL: From Visual Motion to Precise Action14 Oct 2026
- 2026Urbex: Agentic Spatial Grounding for City-Scale 3D Scenes13 Oct 2026
- 2026UniMetric: Universal Metric Scale Recovery for Visual Geometry Foundation Models12 Oct 2026
- 2026EmbPASS: Towards Cross-Embodiment Open Panoramic Segmentation2 Oct 2026
- 2026CitySTAR: Structured and Topology-Aware Reasoning for Open-Vocabulary Urban 3D Grounding17 Sep 2026
- 2026Qwen-3D: A Generalist 3D Vision-Language Model for Spatial Understanding4 Aug 2026
- 2026EventDrive: Event Cameras for Vision-Language Driving Intelligence16 Jun 2026
- 2026OmniLiDAR: A Unified Diffusion Framework for Multi-Domain 3D LiDAR Generation13 May 2026
- 2026WildDet3D: Scaling Promptable 3D Detection in the Wild9 Apr 2026
- 2026AdaSFormer: Adaptive Serialized Transformers for Monocular Semantic Scene Completion from Indoor Environments26 Mar 2026
- 2025Vision-Language-Action Models for Autonomous Driving: Past, Present, and Future18 Dec 2025
- 2025U4D: Uncertainty-Aware 4D World Modeling from LiDAR Sequences2 Dec 2025
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