CitySTAR: Structured and Topology-Aware Reasoning for Open-Vocabulary Urban 3D Grounding

arXiv:2609.19911 · cs.CV · Submitted 2026-09-17 · Read on arXiv

cs.CV

Submitted: 2026-09-17

Updated: 2026-09-17

Terminology

• Grounding — 77× in this paper · explained in 3 episodes
• Verification — 29× in this paper · explained in 2 episodes
• Visual Grounding — 18× in this paper · explained in 2 episodes
• Hypergraph — 14× in this paper · explained in 2 episodes
• Consistency — 10× in this paper · explained in 3 episodes
• Benchmark — 8× in this paper · explained in 2 episodes
• Point Clouds — 7× in this paper · explained in 2 episodes
• Alignment — 5× in this paper · explained in 1 episode
• Accuracy — 3× in this paper · explained in 1 episode
• Training-Free Framework — 3× in this paper · explained in 2 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Ablation study — 2× in this paper · explained in 1 episode
• Embeddings — 2× in this paper · explained in 2 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Instruction Tuning — 2× in this paper · explained in 2 episodes
• Interpretability — 2× in this paper · explained in 15 episodes
• Novel Descriptions — 2× in this paper
• Novel Objects — 2× in this paper
• Structured Reasoning — 2× in this paper · explained in 3 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Computational overhead — 1× in this paper · explained in 2 episodes
• Digital Twin — 1× in this paper · explained in 5 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Gaussian Splatting — 1× in this paper · explained in 4 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• IEEE International Conference on Robotics and Automation — 1× in this paper
• Multimodal Reasoning — 1× in this paper · explained in 5 episodes
• Point Cloud Data — 1× in this paper · explained in 2 episodes
• Semantic Similarity — 1× in this paper · explained in 2 episodes
• Vision-Language Models (VLMs) — 1× in this paper · explained in 6 episodes

Sources

• Emergent Visual Grounding in Large Multimodal Models Without Grounding Supervision
• 3DCity-LLM: Empowering Multi-modality Large Language Models for 3D City-scale Perception and Understanding
• Scene-LLM: Extending Language Model for 3D Visual Understanding and Reasoning
• Point-Bind & Point-LLM: Aligning Point Cloud with Multi-modality for 3D Understanding, Generation, and Instruction Following
• 3EED: Ground Everything Everywhere in 3D
• CityRefer: Geography-aware 3D Visual Grounding Dataset on City-scale Point Cloud Data
• Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models

Related papers

• Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
• AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories
• Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
• MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal MRI Segmentation
• TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
• A Survey on Efficient Vision-Language-Action Models