LaVIDE: A Language-Vision Discriminator for Detecting Changes in Satellite Image with Map References Article Swipe
Shuguo Jiang
,
Fang Xu
,
Sen Jia
,
Gui-Song Xia
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2411.19758
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2411.19758
Change detection, which typically relies on the comparison of bi-temporal images, is significantly hindered when only a single image is available. Comparing a single image with an existing map, such as OpenStreetMap, which is continuously updated through crowd-sourcing, offers a viable solution to this challenge. Unlike images that carry low-level visual details of ground objects, maps convey high-level categorical information. This discrepancy in abstraction levels complicates the alignment and comparison of the two data types. In this paper, we propose a \textbf{La}nguage-\textbf{VI}sion \textbf{D}iscriminator for d\textbf{E}tecting changes in satellite image with map references, namely \ours{}, which leverages language to bridge the information gap between maps and images. Specifically, \ours{} formulates change detection as the problem of ``{\textit Does the pixel belong to [class]?}'', aligning maps and images within the feature space of the language-vision model to associate high-level map categories with low-level image details. Moreover, we build a mixture-of-experts discriminative module, which compares linguistic features from maps with visual features from images across various semantic perspectives, achieving comprehensive semantic comparison for change detection. Extensive evaluation on four benchmark datasets demonstrates that \ours{} can effectively detect changes in satellite image with map references, outperforming state-of-the-art change detection algorithms, e.g., with gains of about $13.8$\% on the DynamicEarthNet dataset and $4.3$\% on the SECOND dataset.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2411.19758
- https://arxiv.org/pdf/2411.19758
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4405031496
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4405031496Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2411.19758Digital Object Identifier
- Title
-
LaVIDE: A Language-Vision Discriminator for Detecting Changes in Satellite Image with Map ReferencesWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-11-29Full publication date if available
- Authors
-
Shuguo Jiang, Fang Xu, Sen Jia, Gui-Song XiaList of authors in order
- Landing page
-
https://arxiv.org/abs/2411.19758Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2411.19758Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2411.19758Direct OA link when available
- Concepts
-
Discriminator, Image (mathematics), Computer vision, Satellite, Computer science, Artificial intelligence, Satellite image, Remote sensing, Geography, Detector, Physics, Telecommunications, AstronomyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.\textbf{La}nguage-\textbf{VI}sion | 81 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile |