Object Detection in Optical Remote Sensing Images: A Survey and A New Benchmark
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Summary
A comprehensive review of the recent deep learning based object detection progress in both the computer vision and earth observation communities is provided and a large-scale, publicly available benchmark for object DetectIon in Optical Remote sensing images is proposed, which is named as DIOR.
- Type
- article
- Published
- 2019-08-31
- Cited by
- 2,254
- References
- 131
- Access
- Open access
- OpenAlex
- https://openalex.org/W2992240579
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:202541171
Keywords
Benchmark (surveying), Computer science, Object detection, Object (grammar), Artificial intelligence
References
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- You Only Look Once: Unified, Real-Time Object Detection
- Fast Multiclass Vehicle Detection on Aerial Images
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- Fully convolutional networks for semantic segmentation
- Rotation-Invariant Object Detection in High-Resolution Satellite Imagery Using Superpixel-Based Deep Hough Forests
- Object Detection via a Multi-region and Semantic Segmentation-Aware CNN Model
- segDeepM: Exploiting segmentation and context in deep neural networks for object detection
- Strategies for training large scale neural network language models
- VHR Object Detection Based on Structural Feature Extraction and Query Expansion
- Multi-class geospatial object detection and geographic image classification based on collection of part detectors
- Object detection in remote sensing imagery using a discriminatively trained mixture model
- Efficient, simultaneous detection of multi-class geospatial targets based on visual saliency modeling and discriminative learning of sparse coding
- Learning Hierarchical Features for Scene Labeling
- Automatic landslide detection from remote-sensing imagery using a scene classification method based on BoVW and pLSA
- The Pascal Visual Object Classes (VOC) Challenge
- The Pascal Visual Object Classes Challenge: A Retrospective
- Detection of seals in remote sensing images using features extracted from deep convolutional neural networks
- Elliptic Fourier transformation-based histograms of oriented gradients for rotationally invariant object detection in remote-sensing images
- Detection of Compound Structures Using a Gaussian Mixture Model With Spectral and Spatial Constraints
Cited by
- Deep feature learning versus shallow feature learning systems for joint use of airborne thermal hyperspectral and visible remote sensing data
- Learning Modulated Loss for Rotated Object Detection
- Oriented Objects as pairs of Middle Lines
- Object Detection in Remote Sensing Images Based on Improved Bounding Box Regression and Multi-Level Features Fusion
- ERA: A Data Set and Deep Learning Benchmark for Event Recognition in Aerial Videos [Software and Data Sets]
- Automatic Fabric Defect Detection Using Cascaded Mixed Feature Pyramid with Guided Localization
- Cross-Scale Feature Fusion for Object Detection in Optical Remote Sensing Images
- Small-Object Detection in Remote Sensing Images with End-to-End Edge-Enhanced GAN and Object Detector Network
- Multi-Scale Feature Integrated Attention-Based Rotation Network for Object Detection in VHR Aerial Images
- A Multi-Scale Water Extraction Convolutional Neural Network (MWEN) Method for GaoFen-1 Remote Sensing Images
- Deep Nearest Neighbor Anomaly Detection
- A New Benchmark and an Attribute-Guided Multilevel Feature Representation Network for Fine-Grained Ship Classification in Optical Remote Sensing Images
- High-Quality Proposals for Weakly Supervised Object Detection
- Progressive Contextual Instance Refinement for Weakly Supervised Object Detection in Remote Sensing Images
- Remote Sensing Image Scene Classification Meets Deep Learning: Challenges, Methods, Benchmarks, and Opportunities
- SCRDet++: Detecting Small, Cluttered and Rotated Objects via Instance-Level Feature Denoising and Rotation Loss Smoothing
- U-Net-Id, an Instance Segmentation Model for Building Extraction from Satellite Images - Case Study in the Joanópolis City, Brazil
- Generating Natural Adversarial Remote Sensing Images
- Knowledge discovery from remote sensing images: A review
- Object Detection and Image Segmentation with Deep Learning on Earth Observation Data: A Review-Part I: Evolution and Recent Trends
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