Z3D: Zero-Shot 3D Visual Grounding from Images

• URL: http://arxiv.org/abs/2602.03361v1
• Date: Tue, 03 Feb 2026 10:35:18 GMT
• Title: Z3D: Zero-Shot 3D Visual Grounding from Images
• Authors: Nikita Drozdov, Andrey Lemeshko, Nikita Gavrilov, Anton Konushin, Danila Rukhovich, Maksim Kolodiazhnyi,
• Abstract summary: 3D visual grounding (3DVG) aims to localize objects in a 3D scene based on natural language queries.<n>We introduce Z3D, a universal grounding pipeline that flexibly operates on multi-view images.
• Score: 7.756226313216256
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 3D visual grounding (3DVG) aims to localize objects in a 3D scene based on natural language queries. In this work, we explore zero-shot 3DVG from multi-view images alone, without requiring any geometric supervision or object priors. We introduce Z3D, a universal grounding pipeline that flexibly operates on multi-view images while optionally incorporating camera poses and depth maps. We identify key bottlenecks in prior zero-shot methods causing significant performance degradation and address them with (i) a state-of-the-art zero-shot 3D instance segmentation method to generate high-quality 3D bounding box proposals and (ii) advanced reasoning via prompt-based segmentation, which utilizes full capabilities of modern VLMs. Extensive experiments on the ScanRefer and Nr3D benchmarks demonstrate that our approach achieves state-of-the-art performance among zero-shot methods. Code is available at https://github.com/col14m/z3d .

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