mlsanityData to 14 Oct 2026

Recov-Vision: Linking Street View Imagery and Vision-Language Models for Post-Disaster Recovery

arXiv 2509.20628 ↗First posted 25 Sep 2025cs.CVcited by 2

On the map: Multimodal LLMs / vision-language models → Embodied and 3D vision-language models

Abstract (arXiv)

Building-level occupancy after disasters is vital for triage, inspections, utility re-energization, and equitable resource allocation. Overhead imagery provides rapid coverage but often misses facade and access cues that determine habitability, while street-view imagery captures those details but is sparse and difficult to align with parcels. We present FacadeTrack, a street-level, language-guided framework that links panoramic video to parcels, rectifies views to facades, and elicits interpretable attributes (for example, entry blockage, temporary coverings, localized debris) that drive two decision strategies: a transparent one-stage rule and a two-stage design that separates perception from conservative reasoning. Evaluated across two post-Hurricane Helene surveys, the two-stage approach achieves a precision of 0.927, a recall of 0.781, and an F-1 score of 0.848, compared with the one-stage baseline at a precision of 0.943, a recall of 0.728, and an F-1 score of 0.822. Beyond accuracy, intermediate attributes and spatial diagnostics reveal where and why residual errors occur, enabling targeted quality control. The pipeline provides auditable, scalable occupancy assessments suitable for integration into geospatial and emergency-management workflows.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Placed in Embodied and 3D vision-language models, one of 16 directions in Multimodal LLMs / vision-language models. Builds on 18 of its 53 references that are in the map. First posted on arXiv 25 Sep 2025.

Builds on

18 of 53 references.

Closest ancestors · 4

Same direction, newest first

  1. 2025Automated Wildfire Damage Assessment from Multi view Ground level Imagery Via Vision Language Models2 Sep
  2. 2025Effective Damage Data Generation by Fusing Imagery with Human Knowledge Using Vision-Language Models2 Aug
  3. 2025DisasterM3: A Remote Sensing Vision-Language Dataset for Disaster Damage Assessment and Response27 May
  4. 2025Vision-Language Modeling Meets Remote Sensing: Models, Datasets and Perspectives20 May

Other references · 14

  1. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  2. 2020FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understandingcited by 181
  3. 2022Large-scale Building Damage Assessment using a Novel Hierarchical Transformer Architecture on Satellite Imagescited by 24
  4. 2024ChangeChat: An Interactive Model for Remote Sensing Change Analysis via Multimodal Instruction Tuningcited by 23
  5. 2021BDANet: Multiscale Convolutional Neural Network with Cross-directional Attention for Building Damage Assessment from Satellite Imagescited by 19
  6. 2022SiamixFormer: a fully-transformer Siamese network with temporal Fusion for accurate building detection and change detection in bi-temporal remote sensing imagescited by 10
  7. 2024ELEV-VISION-SAM: Integrated Vision Language and Foundation Model for Automated Estimation of Building Lowest Floor Elevationcited by 9
  8. 2025OpenFACADES: An Open Framework for Architectural Caption and Attribute Data Enrichment via Street View Imagerycited by 8
  9. 2025Hyperlocal disaster damage assessment using bi-temporal street-view imagery and pre-trained vision modelscited by 8
  10. 2025DamageCAT: A Deep Learning Transformer Framework for Typology-Based Post-Disaster Building Damage Categorizationcited by 8
  11. 2020Deep Learning-based Aerial Image Segmentation with Open Data for Disaster Impact Assessmentcited by 5
  12. 2024Post-hurricane building damage assessment using street-view imagery and structured data: A multi-modal deep learning approachcited by 4
2 more
  1. 2023Street View Data Collection Design for Disaster Reconnaissancecited by 2
  2. 2024Open-source data pipeline for street-view images: a case study on community mobility during COVID-19 pandemiccited by 1

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.

  1. 2026CrisiSense-RAG: Crisis Sensing Multimodal Retrieval-Augmented Generation for Rapid Disaster Impact Assessmentcited by 3
  2. 2025GraphFire-X: Physics-Informed Graph Attention Networks and Structural Gradient Boosting for Building-Scale Wildfire Preparedness at the Wildland-Urban Interfacecited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026Satellite-to-Street: Synthesizing Post-Disaster Views from Satellite Imagery via Generative Vision Models
  2. 2026DisasterInsight: A Building-Centric Benchmark for Evaluating Vision--Language Models in Disaster Response
  3. 2026You Cannot Photograph the Same Street Twice: Reliability Limits in Vision-Language Measurement of Urban Change
  4. 2026Benchmarks for Vision-Language Models in Urban Perception Should Be Reliability-Aware and Negotiated
  5. 2026A Decade of PhotoMappers: A Longitudinal Study of Crowdsourced Disaster Photos Geolocalization with Vision-Language Models and Geospatial Reasoning
  6. 2025Interpretable Multimodal Framework for Human-Centered Street Assessment: Integrating Visual-Language Models for Perceptual Urban Diagnostics
  7. 2026Keep Your Friends Close, and the Right Neighbours Closer: Disaster-Conditioned Kernel-Regularized Graph Attention for Building Damage Classification
  8. 2025Do Vision-Language Models See Urban Scenes as People Do? An Urban Perception Benchmark