A context-scale-aware detector and a new benchmark for remote sensing small weak object detection in unmanned aerial vehicle images
Due to the fast development of imaging sensors used in remote sensing, high-resolution images can increasingly exhibit fine-grained information on the Earth’s surface, which makes detecting real-world small-scale, weak-feature-response geospatial targets possible. Detecting these small weak targets...
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-08-01
|
| Series: | International Journal of Applied Earth Observations and Geoinformation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843222001595 |
| _version_ | 1798036778949541888 |
|---|---|
| author | Wei Han Jun Li Sheng Wang Yi Wang Jining Yan Runyu Fan Xiaohan Zhang Lizhe Wang |
| author_facet | Wei Han Jun Li Sheng Wang Yi Wang Jining Yan Runyu Fan Xiaohan Zhang Lizhe Wang |
| author_sort | Wei Han |
| collection | DOAJ |
| description | Due to the fast development of imaging sensors used in remote sensing, high-resolution images can increasingly exhibit fine-grained information on the Earth’s surface, which makes detecting real-world small-scale, weak-feature-response geospatial targets possible. Detecting these small weak targets is of great significance in some applications. Although remarkable efforts have been made to develop small weak object detection, existing works mainly focus on processing satellite images. Unmanned aerial vehicle (UAV) remote sensing images have very high resolutions and short revisit times, thus making them a novel kind of data for Earth observation, and are more rarely studied. Meanwhile, due to the characteristics of UAV images, some problems, such as high intra-class variations, complex contexts, and noise, are pronounced. To promote the remote sensing detection of small weak objects in UAV images, this paper proposes a 10-category UAV object detection dataset, namely UAVOD-10, 11 The dataset is available at https://github.com/weihancug/10-category-UAV-small-weak-object-detection-dataset-UAVOD10. and a novel context-scale-aware detector, namely, CSADet. The objects in UAVOD-10 are sufficiently varied and affected by imaging conditions and their contexts. Some of them, such as cable towers, wells, and cultivation mesh cages, have small scales and weak feature responses, making them difficult to recognize. To locate these kinds of objects efficiently, CSADet first utilizes a context-aware module that can jointly explore valuable local and global contexts and then applies a multi-scale feature refinement module to extract and share all the levels of the features. Extensive experiments on the proposed UAVOD-10 dataset demonstrate its remarkable detection performance. |
| first_indexed | 2024-04-11T21:17:41Z |
| format | Article |
| id | doaj.art-868d1c5b388343ed97fdf581043b1613 |
| institution | Directory Open Access Journal |
| issn | 1569-8432 |
| language | English |
| last_indexed | 2024-04-11T21:17:41Z |
| publishDate | 2022-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj.art-868d1c5b388343ed97fdf581043b16132022-12-22T04:02:45ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322022-08-01112102966A context-scale-aware detector and a new benchmark for remote sensing small weak object detection in unmanned aerial vehicle imagesWei Han0Jun Li1Sheng Wang2Yi Wang3Jining Yan4Runyu Fan5Xiaohan Zhang6Lizhe Wang7School of Computer Science, China University of Geosciences, Wuhan, 430078, ChinaSchool of Computer Science, China University of Geosciences, Wuhan, 430078, ChinaSchool of Computer Science, China University of Geosciences, Wuhan, 430078, ChinaInstitute of Geophysics and Geomatics, China University of Geosciences, Wuhan, 430074, ChinaSchool of Computer Science, China University of Geosciences, Wuhan, 430078, ChinaSchool of Computer Science, China University of Geosciences, Wuhan, 430078, ChinaSchool of Computer Science, China University of Geosciences, Wuhan, 430078, ChinaSchool of Computer Science, China University of Geosciences, Wuhan, 430078, China; Corresponding author.Due to the fast development of imaging sensors used in remote sensing, high-resolution images can increasingly exhibit fine-grained information on the Earth’s surface, which makes detecting real-world small-scale, weak-feature-response geospatial targets possible. Detecting these small weak targets is of great significance in some applications. Although remarkable efforts have been made to develop small weak object detection, existing works mainly focus on processing satellite images. Unmanned aerial vehicle (UAV) remote sensing images have very high resolutions and short revisit times, thus making them a novel kind of data for Earth observation, and are more rarely studied. Meanwhile, due to the characteristics of UAV images, some problems, such as high intra-class variations, complex contexts, and noise, are pronounced. To promote the remote sensing detection of small weak objects in UAV images, this paper proposes a 10-category UAV object detection dataset, namely UAVOD-10, 11 The dataset is available at https://github.com/weihancug/10-category-UAV-small-weak-object-detection-dataset-UAVOD10. and a novel context-scale-aware detector, namely, CSADet. The objects in UAVOD-10 are sufficiently varied and affected by imaging conditions and their contexts. Some of them, such as cable towers, wells, and cultivation mesh cages, have small scales and weak feature responses, making them difficult to recognize. To locate these kinds of objects efficiently, CSADet first utilizes a context-aware module that can jointly explore valuable local and global contexts and then applies a multi-scale feature refinement module to extract and share all the levels of the features. Extensive experiments on the proposed UAVOD-10 dataset demonstrate its remarkable detection performance.http://www.sciencedirect.com/science/article/pii/S1569843222001595Remote sensingObject detectionUnmanned aerial vehicleHigh-resolution remote sensing |
| spellingShingle | Wei Han Jun Li Sheng Wang Yi Wang Jining Yan Runyu Fan Xiaohan Zhang Lizhe Wang A context-scale-aware detector and a new benchmark for remote sensing small weak object detection in unmanned aerial vehicle images International Journal of Applied Earth Observations and Geoinformation Remote sensing Object detection Unmanned aerial vehicle High-resolution remote sensing |
| title | A context-scale-aware detector and a new benchmark for remote sensing small weak object detection in unmanned aerial vehicle images |
| title_full | A context-scale-aware detector and a new benchmark for remote sensing small weak object detection in unmanned aerial vehicle images |
| title_fullStr | A context-scale-aware detector and a new benchmark for remote sensing small weak object detection in unmanned aerial vehicle images |
| title_full_unstemmed | A context-scale-aware detector and a new benchmark for remote sensing small weak object detection in unmanned aerial vehicle images |
| title_short | A context-scale-aware detector and a new benchmark for remote sensing small weak object detection in unmanned aerial vehicle images |
| title_sort | context scale aware detector and a new benchmark for remote sensing small weak object detection in unmanned aerial vehicle images |
| topic | Remote sensing Object detection Unmanned aerial vehicle High-resolution remote sensing |
| url | http://www.sciencedirect.com/science/article/pii/S1569843222001595 |
| work_keys_str_mv | AT weihan acontextscaleawaredetectorandanewbenchmarkforremotesensingsmallweakobjectdetectioninunmannedaerialvehicleimages AT junli acontextscaleawaredetectorandanewbenchmarkforremotesensingsmallweakobjectdetectioninunmannedaerialvehicleimages AT shengwang acontextscaleawaredetectorandanewbenchmarkforremotesensingsmallweakobjectdetectioninunmannedaerialvehicleimages AT yiwang acontextscaleawaredetectorandanewbenchmarkforremotesensingsmallweakobjectdetectioninunmannedaerialvehicleimages AT jiningyan acontextscaleawaredetectorandanewbenchmarkforremotesensingsmallweakobjectdetectioninunmannedaerialvehicleimages AT runyufan acontextscaleawaredetectorandanewbenchmarkforremotesensingsmallweakobjectdetectioninunmannedaerialvehicleimages AT xiaohanzhang acontextscaleawaredetectorandanewbenchmarkforremotesensingsmallweakobjectdetectioninunmannedaerialvehicleimages AT lizhewang acontextscaleawaredetectorandanewbenchmarkforremotesensingsmallweakobjectdetectioninunmannedaerialvehicleimages AT weihan contextscaleawaredetectorandanewbenchmarkforremotesensingsmallweakobjectdetectioninunmannedaerialvehicleimages AT junli contextscaleawaredetectorandanewbenchmarkforremotesensingsmallweakobjectdetectioninunmannedaerialvehicleimages AT shengwang contextscaleawaredetectorandanewbenchmarkforremotesensingsmallweakobjectdetectioninunmannedaerialvehicleimages AT yiwang contextscaleawaredetectorandanewbenchmarkforremotesensingsmallweakobjectdetectioninunmannedaerialvehicleimages AT jiningyan contextscaleawaredetectorandanewbenchmarkforremotesensingsmallweakobjectdetectioninunmannedaerialvehicleimages AT runyufan contextscaleawaredetectorandanewbenchmarkforremotesensingsmallweakobjectdetectioninunmannedaerialvehicleimages AT xiaohanzhang contextscaleawaredetectorandanewbenchmarkforremotesensingsmallweakobjectdetectioninunmannedaerialvehicleimages AT lizhewang contextscaleawaredetectorandanewbenchmarkforremotesensingsmallweakobjectdetectioninunmannedaerialvehicleimages |