mlsanityData to 14 Oct 2026

iSAID: A Large-scale Dataset for Instance Segmentation in Aerial Images

arXiv 1905.12886 ↗First posted 30 May 2019cs.CV cs.LGcited by 197

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Abstract (arXiv)

Existing Earth Vision datasets are either suitable for semantic segmentation or object detection. In this work, we introduce the first benchmark dataset for instance segmentation in aerial imagery that combines instance-level object detection and pixel-level segmentation tasks. In comparison to instance segmentation in natural scenes, aerial images present unique challenges e.g., a huge number of instances per image, large object-scale variations and abundant tiny objects. Our large-scale and densely annotated Instance Segmentation in Aerial Images Dataset (iSAID) comes with 655,451 object instances for 15 categories across 2,806 high-resolution images. Such precise per-pixel annotations for each instance ensure accurate localization that is essential for detailed scene analysis. Compared to existing small-scale aerial image based instance segmentation datasets, iSAID contains 15× the number of object categories and 5× the number of instances. We benchmark our dataset using two popular instance segmentation approaches for natural images, namely Mask R-CNN and PANet. In our experiments we show that direct application of off-the-shelf Mask R-CNN and PANet on aerial images provide suboptimal instance segmentation results, thus requiring specialized solutions from the research community. The dataset is publicly available at: https://captain-whu.github.io/iSAID/index.html

Key facts. Cited by 197 papers in the map (data through 14 Oct 2026). First posted on arXiv 30 May 2019.

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Citing papers per year: 2021: 18; 2022: 22; 2023: 34; 2024: 43; 2025: 48; 2026: 32.

197 papers.

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  1. 2023RemoteCLIP: A Vision Language Foundation Model for Remote Sensingcited by 363
  2. 2021LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentationcited by 261
  3. 2022SegNeXt: Rethinking Convolutional Attention Design for Semantic Segmentationcited by 252
  4. 2023CAT-Seg: Cost Aggregation for Open-Vocabulary Semantic Segmentationcited by 219
  5. 2023SkySense: A Multi-Modal Remote Sensing Foundation Model Towards Universal Interpretation for Earth Observation Imagerycited by 205
  6. 2021Object Detection in Aerial Images: A Large-Scale Benchmark and Challengescited by 204
  7. 2023SegGPT: Segmenting Everything In Contextcited by 194
  8. 2024EarthGPT: A Universal Multi-modal Large Language Model for Multi-sensor Image Comprehension in Remote Sensing Domaincited by 184
  9. 2022SatlasPretrain: A Large-Scale Dataset for Remote Sensing Image Understandingcited by 167
  10. 2022Advancing Plain Vision Transformer Towards Remote Sensing Foundation Modelcited by 149
  11. 2023RepViT: Revisiting Mobile CNN From ViT Perspectivecited by 123
  12. 2022An Empirical Study of Remote Sensing Pretrainingcited by 105
38 more
  1. 2023Vision-Language Models in Remote Sensing: Current Progress and Future Trendscited by 93
  2. 2021Open-Vocabulary Instance Segmentation via Robust Cross-Modal Pseudo-Labelingcited by 84
  3. 2022DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentationcited by 78
  4. 2024HyperSIGMA: Hyperspectral Intelligence Comprehension Foundation Modelcited by 73
  5. 2024PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Modelscited by 68
  6. 2022Transformers in Remote Sensing: A Surveycited by 61
  7. 2021Factors of Influence for Transfer Learning across Diverse Appearance Domains and Task Typescited by 54
  8. 2021Transferability Estimation using Bhattacharyya Class Separabilitycited by 54
  9. 2025UAVs Meet LLMs: Overviews and Perspectives Toward Agentic Low-Altitude Mobilitycited by 49
  10. 2025ThinkGeo: Evaluating Tool-Augmented Agents for Remote Sensing Taskscited by 46
  11. 2022Box-supervised Instance Segmentation with Level Set Evolutioncited by 41
  12. 2024SatSynth: Augmenting Image-Mask Pairs through Diffusion Models for Aerial Semantic Segmentationcited by 41
  13. 2022EarthNets: Empowering AI in Earth Observationcited by 40
  14. 2025RemoteSAM: Towards Segment Anything for Earth Observationcited by 39
  15. 2023SAMRS: Scaling-up Remote Sensing Segmentation Dataset with Segment Anything Modelcited by 38
  16. 2023MosaicFusion: Diffusion Models as Data Augmenters for Large Vocabulary Instance Segmentationcited by 35
  17. 2024Bridge the Points: Graph-based Few-shot Segment Anything Semanticallycited by 35
  18. 2021INTERN: A New Learning Paradigm Towards General Visioncited by 33
  19. 2022How stable are Transferability Metrics evaluations?cited by 30
  20. 2021PointFlow: Flowing Semantics Through Points for Aerial Image Segmentationcited by 29
  21. 2024EarthMarker: A Visual Prompting Multi-modal Large Language Model for Remote Sensingcited by 29
  22. 2025SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensingcited by 26
  23. 2024SegEarth-OV: Towards Training-Free Open-Vocabulary Segmentation for Remote Sensing Imagescited by 25
  24. 2021Transferability Metrics for Selecting Source Model Ensemblescited by 24
  25. 2022Learning Local and Global Temporal Contexts for Video Semantic Segmentationcited by 24
  26. 2023What a MESS: Multi-Domain Evaluation of Zero-Shot Semantic Segmentationcited by 24
  27. 2023AerialFormer: Multi-resolution Transformer for Aerial Image Segmentationcited by 23
  28. 2022Unsupervised Change Detection Based on Image Reconstruction Losscited by 22
  29. 2022Box2Mask: Box-supervised Instance Segmentation via Level-set Evolutioncited by 22
  30. 2024Masked Angle-Aware Autoencoder for Remote Sensing Imagescited by 22
  31. 2022Self-Pair: Synthesizing Changes from Single Source for Object Change Detection in Remote Sensing Imagerycited by 19
  32. 2024Towards Open-Vocabulary Remote Sensing Image Semantic Segmentationcited by 19
  33. 2025A Survey on Remote Sensing Foundation Models: From Vision to Multimodalitycited by 19
  34. 2021Gaussian Bounding Boxes and Probabilistic Intersection-over-Union for Object Detectioncited by 18
  35. 2025Vision-Language Modeling Meets Remote Sensing: Models, Datasets and Perspectivescited by 18
  36. 2023A Survey on Semi-Supervised Semantic Segmentationcited by 17
  37. 2024Discrete Latent Perspective Learning for Segmentation and Detectioncited by 16
  38. 2025RingMoE: Mixture-of-Modality-Experts Multi-Modal Foundation Models for Universal Remote Sensing Image Interpretationcited by 16

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