mlsanityData to 7 Oct 2026

GeoLLaVA: Efficient Fine-Tuned Vision-Language Models for Temporal Change Detection in Remote Sensing

arXiv 2410.19552 ↗First posted 25 Oct 2024cs.CVcited by 13

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

Abstract (arXiv)

Detecting temporal changes in geographical landscapes is critical for applications like environmental monitoring and urban planning. While remote sensing data is abundant, existing vision-language models (VLMs) often fail to capture temporal dynamics effectively. This paper addresses these limitations by introducing an annotated dataset of video frame pairs to track evolving geographical patterns over time. Using fine-tuning techniques like Low-Rank Adaptation (LoRA), quantized LoRA (QLoRA), and model pruning on models such as Video-LLaVA and LLaVA-NeXT-Video, we significantly enhance VLM performance in processing remote sensing temporal changes. Results show significant improvements, with the best performance achieving a BERT score of 0.864 and ROUGE-1 score of 0.576, demonstrating superior accuracy in describing land-use transformations.

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). Placed in Embodied and 3D vision-language models, one of 16 directions in Multimodal LLMs / vision-language models. Builds on 7 of its 38 references that are in the map. First posted on arXiv 25 Oct 2024.

Builds on

7 of 38 references.

Closest ancestors · 1

Same direction, newest first

  1. 2023RSGPT: A Remote Sensing Vision Language Model and Benchmark28 Jul

Other references · 6

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,462
  3. 2023Video-LLaVA: Learning United Visual Representation by Alignment Before Projectioncited by 1,385
  4. 2023Vision-Language Models for Vision Tasks: A Surveycited by 834
  5. 2018SpaceNet: A Remote Sensing Dataset and Challenge Seriescited by 178
  6. 2024Towards Temporal Change Explanations from Bi-Temporal Satellite Imagescited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 10; 2026: 2.

13 papers.

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  1. 2025Vision-Language Models for Edge Networks: A Comprehensive Surveycited by 29
  2. 2024Remote Sensing SpatioTemporal Vision-Language Models: A Comprehensive Surveycited by 22
  3. 2025DynamicVL: Benchmarking Multimodal Large Language Models for Dynamic City Understandingcited by 17
  4. 2025Robust Change Captioning in Remote Sensing: SECOND-CC Dataset and MModalCC Frameworkcited by 8
  5. 2025VectorLLM: Human-like Extraction of Structured Building Contours vis Multimodal LLMscited by 3
  6. 2026Earth-OneVision: Extending Remote Sensing Multimodal Large Language Models to More Sensor Modalities and Taskscited by 3
  7. 2025Remote Sensing Large Vision-Language Model: Semantic-augmented Multi-level Alignment and Semantic-aware Expert Modelingcited by 2
  8. 2025ChatENV: An Interactive Vision-Language Model for Sensor-Guided Environmental Monitoring and Scenario Simulationcited by 2
  9. 2025Animation Needs Attention: A Holistic Approach to Slides Animation Comprehension with Visual-Language Modelscited by 1
  10. 2025TimeSenCLIP: A Time Series Vision-Language Model for Remote Sensingcited by 1
  11. 2025A Novel Trustworthy Video Summarization Algorithm Through a Mixture of LoRA Expertscited by 0
  12. 2025Operational Change Detection for Geographical Information: Overview and Challengescited by 0
1 more
  1. 2026LongEarth-R1: Benchmarking and Aligning Vision-Language Models for Long-Horizon Earth Observation Reasoningcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Towards Comprehensive Interactive Change Understanding in Remote Sensing: A Large-scale Dataset and Dual-granularity Enhanced VLM
  2. 2024ChangeChat: An Interactive Model for Remote Sensing Change Analysis via Multimodal Instruction Tuning
  3. 2026Revisiting Change VQA in Remote Sensing with Structured and Native Multimodal Qwen Models
  4. 2026Decoding the Delta: Unifying Remote Sensing Change Detection and Understanding with Multimodal Large Language Models
  5. 2025BTCChat: Advancing Remote Sensing Bi-temporal Change Captioning with Multimodal Large Language Model
  6. 2024GEOBench-VLM: Benchmarking Vision-Language Models for Geospatial Tasks
  7. 2025ViLaCD-R1: A Vision-Language Framework for Semantic Change Detection in Remote Sensing
  8. 2024TEOChat: A Large Vision-Language Assistant for Temporal Earth Observation Data