Research map / 3D vision / Face and shape
VLS: A Vision-Language-Shape Model for Open-Vocabulary Partonomic 3D Reconstruction
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AI-extracted summary. Written by AI from the paper's abstract only. Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Introduces open-vocabulary partonomic reconstruction, reconstructing an object and its named semantic parts from a single image, via a vision-language-shape model (VLS).
Problem
Single-view 3D reconstruction typically recovers whole-object geometry and ignores semantic parts, which are important for fine-grained 3D perception; the paper targets reconstructing object and part geometry given an image and arbitrary part names.
Approach
Defines the task of open-vocabulary partonomic reconstruction: given a single image and a set of part names, jointly reconstruct the whole object and its named parts. The VLS model is proposed for this task; the abstract shown is truncated, so further technical details are not available.
Limitations
- Only the truncated abstract was available; full method and results are unknown
Closest papers by meaning
- Learning Partonomic 3D Reconstruction from Image Collections (CVPR 2025 · similarity 0.92)
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- Know Your Neighbors: Improving Single-View Reconstruction via Spatial Vision-Language Reasoning (CVPR 2024 · similarity 0.89)
- OpenLex3D: A Tiered Benchmark for Open-Vocabulary 3D Scene Representations (NeurIPS 2025 · similarity 0.88)
- PartDistill: 3D Shape Part Segmentation by Vision-Language Model Distillation (CVPR 2024 · similarity 0.88)
- 3D-PLOT-LLM: Part-Level Object Tokens for 3D Large Language Models (NeurIPS 2026 · similarity 0.88)
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