{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T00:57:15Z","timestamp":1760230635064,"version":"build-2065373602"},"reference-count":63,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2022,7,29]],"date-time":"2022-07-29T00:00:00Z","timestamp":1659052800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Natural Science Foundation of Shanghai","award":["22ZR1427000","61602296","18CG54"],"award-info":[{"award-number":["22ZR1427000","61602296","18CG54"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China (CN)","doi-asserted-by":"publisher","award":["22ZR1427000","61602296","18CG54"],"award-info":[{"award-number":["22ZR1427000","61602296","18CG54"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shanghai Education Development Foundation and Shanghai Municipal Education Commission","award":["22ZR1427000","61602296","18CG54"],"award-info":[{"award-number":["22ZR1427000","61602296","18CG54"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In recent years, significant progress has been made in arbitrary-oriented object detection. Different from natural images, object detection in aerial images remains its problems and challenges. Current feature enhancement strategies in this field mainly focus on enhancing the local critical response of the target while ignoring the target\u2019s contextual information, which is indispensable for detecting remote sensing targets in complex backgrounds. In this paper, we innovatively combine semantic edge detection with arbitrary-oriented object detection and propose a feature enhancement network base on a semantic edge supervision module (SES) that realizes an attention-like mechanism in three dimensions of space, channel, and pyramid level. It helps the network pay attention to the edge features of targets at multiple scales to obtain more regression clues. Furthermore, to solve the problem of dense objects with different directions in remote sensing images, we propose a rotation-invariant spatial pooling pyramid (RISPP) to extract the features of objects from multiple orientations. Based on the two feature enhancement modules, we named the network SE2-Det; extensive experiments on large public datasets of aerial images (DOTA and UCAS-AOD) validate our approach\u2019s effectiveness and demonstrate our detector\u2019s superior performance.<\/jats:p>","DOI":"10.3390\/rs14153637","type":"journal-article","created":{"date-parts":[[2022,8,1]],"date-time":"2022-08-01T04:04:00Z","timestamp":1659326640000},"page":"3637","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Semantic-Edge-Supervised Single-Stage Detector for Oriented Object Detection in Remote Sensing Imagery"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1376-1509","authenticated-orcid":false,"given":"Dujuan","family":"Cao","sequence":"first","affiliation":[{"name":"College of Information and Engineering, Shanghai Maritime University, Shanghai 201306, China"}]},{"given":"Changming","family":"Zhu","sequence":"additional","affiliation":[{"name":"College of Information and Engineering, Shanghai Maritime University, Shanghai 201306, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8231-4024","authenticated-orcid":false,"given":"Xinxin","family":"Hu","sequence":"additional","affiliation":[{"name":"College of Information and Engineering, Shanghai Maritime University, Shanghai 201306, China"}]},{"given":"Rigui","family":"Zhou","sequence":"additional","affiliation":[{"name":"College of Information and Engineering, Shanghai Maritime University, Shanghai 201306, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Girshick, R., Donahue, J., Darrell, T., and Malik, J. (2014, January 23\u201328). Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation. Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, Columbus, OH, USA.","DOI":"10.1109\/CVPR.2014.81"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Girshick, R. (2015, January 7\u201312). Fast R-CNN. Proceedings of the IEEE International Conference on Computer Vision, Boston, MA, USA.","DOI":"10.1109\/ICCV.2015.169"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","article-title":"Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks","volume":"39","author":"Ren","year":"2017","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"He, K., Gkioxari, G., Doll\u00e1r, P., and Girshick, R. (2017, January 22\u201329). Mask R-CNN. Proceedings of the 2017 IEEE International Conference on Computer Vision (ICCV), Venice, Italy.","DOI":"10.1109\/ICCV.2017.322"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Cai, Z., and Vasconcelos, N. (2018, January 18\u201323). Cascade R-CNN: Delving Into High Quality Object Detection. Proceedings of the 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA.","DOI":"10.1109\/CVPR.2018.00644"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Redmon, J., Divvala, S., Girshick, R., and Farhadi, A. (2016, January 27\u201330). You Only Look Once: Unified, Real-Time Object Detection. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.91"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Tian, Z., Shen, C., Chen, H., and He, T. (November, January 27). FCOS: Fully Convolutional One-Stage Object Detection. Proceedings of the 2019 IEEE\/CVF International Conference on Computer Vision (ICCV), Seoul, Korea.","DOI":"10.1109\/ICCV.2019.00972"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1109\/TPAMI.2018.2858826","article-title":"Focal Loss for Dense Object Detection","volume":"42","author":"Lin","year":"2020","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Leibe, B., Matas, J., Sebe, N., and Welling, M. (2016, January 11\u201314). SSD: Single Shot MultiBox Detector. Proceedings of the Computer Vision\u2014ECCV, Amsterdam, The Netherlands. Lecture Notes in Computer Science.","DOI":"10.1007\/978-3-319-46478-7"},{"key":"ref_10","first-page":"3163","article-title":"R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object","volume":"35","author":"Yang","year":"2021","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"ref_11","first-page":"5602511","article-title":"Align Deep Features for Oriented Object Detection","volume":"60","author":"Han","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Yang, X., Yang, J., Yan, J., Zhang, Y., Zhang, T., Guo, Z., Sun, X., and Fu, K. (November, January 27). SCRDet: Towards More Robust Detection for Small, Cluttered and Rotated Objects. Proceedings of the 2019 IEEE\/CVF International Conference on Computer Vision (ICCV), Seoul, Korea.","DOI":"10.1109\/ICCV.2019.00832"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Yang, X., Yan, J., Liao, W., Yang, X., Tang, J., and He, T. (2022). SCRDet++: Detecting Small, Cluttered and Rotated Objects via Instance-Level Feature Denoising and Rotation Loss Smoothing. IEEE Trans. Pattern Anal. Mach. Intell., early access.","DOI":"10.1109\/TPAMI.2022.3166956"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Ming, Q., Miao, L., Zhou, Z., Song, J., and Yang, X. (2021). Sparse Label Assignment for Oriented Object Detection in Aerial Images. Remote Sens., 13.","DOI":"10.3390\/rs13142664"},{"key":"ref_15","first-page":"2355","article-title":"Dynamic Anchor Learning for Arbitrary-Oriented Object Detection","volume":"35","author":"Ming","year":"2021","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"ref_16","unstructured":"Yang, X., Yan, J., Ming, Q., Wang, W., Zhang, X., and Tian, Q. (2021, January 18\u201324). Rethinking Rotated Object Detection with Gaussian Wasserstein Distance Loss. Proceedings of the 38th International Conference on Machine Learning, PMLR, Virtual."},{"key":"ref_17","first-page":"18381","article-title":"Learning High-Precision Bounding Box for Rotated Object Detection via Kullback-Leibler Divergence","volume":"Volume 34","author":"Yang","year":"2021","journal-title":"Proceedings of the Advances in Neural Information Processing Systems"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"5605814","DOI":"10.1109\/TGRS.2021.3095186","article-title":"CFC-Net: A Critical Feature Capturing Network for Arbitrary-Oriented Object Detection in Remote-Sensing Images","volume":"60","author":"Ming","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Han, J., Ding, J., Xue, N., and Xia, G.S. (2021, January 20\u201325). ReDet: A Rotation-Equivariant Detector for Aerial Object Detection. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Nashville, TN, USA.","DOI":"10.1109\/CVPR46437.2021.00281"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2148","DOI":"10.1109\/JSTARS.2020.3046482","article-title":"Cross-Layer Attention Network for Small Object Detection in Remote Sensing Imagery","volume":"14","author":"Li","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1109\/TIP.2018.2867198","article-title":"Learning Rotation-Invariant and Fisher Discriminative Convolutional Neural Networks for Object Detection","volume":"28","author":"Cheng","year":"2019","journal-title":"IEEE Trans. Image Process."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Yu, Z., Feng, C., Liu, M.Y., and Ramalingam, S. (2017, January 21\u201326). CASENet: Deep Category-Aware Semantic Edge Detection. Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.191"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Hao, X., Shan, C., Xu, Y., Sun, S., and Xie, L. (2019, January 12\u201317). An Attention-based Neural Network Approach for Single Channel Speech Enhancement. Proceedings of the ICASSP 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, UK.","DOI":"10.1109\/ICASSP.2019.8683169"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Woo, S., Park, J., Lee, J.Y., and Kweon, I.S. (2018, January 8\u201314). CBAM: Convolutional Block Attention Module. Proceedings of the European Conference on Computer Vision (ECCV), Munich, Germany.","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Hou, Q., Zhou, D., and Feng, J. (2021, January 20\u201325). Coordinate Attention for Efficient Mobile Network Design. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Nashville, TN, USA.","DOI":"10.1109\/CVPR46437.2021.01350"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Jiang, B., Luo, R., Mao, J., Xiao, T., and Jiang, Y. (2018, January 8\u201314). Acquisition of Localization Confidence for Accurate Object Detection. Proceedings of the European Conference on Computer Vision (ECCV), Munich, Germany.","DOI":"10.1007\/978-3-030-01264-9_48"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1904","DOI":"10.1109\/TPAMI.2015.2389824","article-title":"Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition","volume":"37","author":"He","year":"2015","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Xia, G.S., Bai, X., Ding, J., Zhu, Z., Belongie, S., Luo, J., Datcu, M., Pelillo, M., and Zhang, L. (2018, January 18\u201323). DOTA: A Large-Scale Dataset for Object Detection in Aerial Images. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA.","DOI":"10.1109\/CVPR.2018.00418"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Zhu, H., Chen, X., Dai, W., Fu, K., Ye, Q., and Jiao, J. (2015, January 27\u201330). Orientation robust object detection in aerial images using deep convolutional neural network. Proceedings of the 2015 IEEE International Conference on Image Processing (ICIP), Quebec City, QC, Canada.","DOI":"10.1109\/ICIP.2015.7351502"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Zhou, Y., Ye, Q., Qiu, Q., and Jiao, J. (2017, January 21\u201326). Oriented Response Networks. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.527"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/0262-8856(83)90006-9","article-title":"On the accuracy of the Sobel edge detector","volume":"1","author":"Kittler","year":"1983","journal-title":"Image Vis. Comput."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1109\/TPAMI.1986.4767851","article-title":"A Computational Approach to Edge Detection","volume":"PAMI-8","author":"Canny","year":"1986","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Hu, Y., Chen, Y., Li, X., and Feng, J. (2019, January 10\u201316). Dynamic feature fusion for semantic edge detection. Proceedings of the 28th International Joint Conference on Artificial Intelligence, (IJCAI\u201919), Macao, China.","DOI":"10.24963\/ijcai.2019\/110"},{"key":"ref_34","unstructured":"Takikawa, T., Acuna, D., Jampani, V., and Fidler, S. (November, January 27). Gated-SCNN: Gated Shape CNNs for Semantic Segmentation. Proceedings of the IEEE\/CVF International Conference on Computer Vision, Seoul, Korea."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Zhen, M., Wang, J., Zhou, L., Li, S., Shen, T., Shang, J., Fang, T., and Quan, L. (2020, January 13\u201319). Joint Semantic Segmentation and Boundary Detection Using Iterative Pyramid Contexts. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Seattle, WA, USA.","DOI":"10.1109\/CVPR42600.2020.01368"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Zhao, J.X., Liu, J.J., Fan, D.P., Cao, Y., Yang, J., and Cheng, M.M. (2019, January 15\u201320). EGNet: Edge Guidance Network for Salient Object Detection. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Long Beach, CA, USA.","DOI":"10.1109\/ICCV.2019.00887"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., and Sun, J. (2016, January 27\u201330). Deep Residual Learning for Image Recognition. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Lin, T.Y., Doll\u00c3\u0105r, P., Girshick, R., He, K., Hariharan, B., and Belongie, S. (2017, January 21\u201326). Feature Pyramid Networks for Object Detection. Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.106"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Sun, Y., and Ye, J. (2019, January 19\u201323). FEDet: Feature Enhancement Single Shot Detector. Proceedings of the 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld\/SCALCOM\/UIC\/ATC\/CBDCom\/IOP\/SCI), Leicester, UK.","DOI":"10.1109\/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00174"},{"key":"ref_40","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, L., and Polosukhin, I. (2017, January 4\u20139). Attention is all you need. Proceedings of the 31st International Conference on Neural Information Processing Systems, Long Beach, CA, USA. NIPS\u201917."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Song, G., Liu, Y., and Wang, X. (2020, January 13\u201319). Revisiting the Sibling Head in Object Detector. Proceedings of the 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, USA.","DOI":"10.1109\/CVPR42600.2020.01158"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"3096","DOI":"10.1109\/TPAMI.2021.3050494","article-title":"Learning to Match Anchors for Visual Object Detection","volume":"44","author":"Zhang","year":"2022","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Xie, S., and Tu, Z. (2015, January 7\u201313). Holistically-Nested Edge Detection. Proceedings of the 2015 IEEE International Conference on Computer Vision (ICCV), Santiago, Chile.","DOI":"10.1109\/ICCV.2015.164"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Acuna, D., Kar, A., and Fidler, S. (2019, January 15\u201320). Devil Is in the Edges: Learning Semantic Boundaries From Noisy Annotations. Proceedings of the 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, CA, USA.","DOI":"10.1109\/CVPR.2019.01133"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Yu, Z., Liu, W., Zou, Y., Feng, C., Ramalingam, S., Kumar, B.V.K.V., and Kautz, J. (2018, January 8\u201314). Simultaneous Edge Alignment and Learning. Proceedings of the European Conference on Computer Vision (ECCV), Munich, Germany.","DOI":"10.1007\/978-3-030-01219-9_24"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"e3","DOI":"10.23915\/distill.00003","article-title":"Deconvolution and Checkerboard Artifacts","volume":"1","author":"Odena","year":"2016","journal-title":"Distill"},{"key":"ref_47","unstructured":"Weiler, M., and Cesa, G. (2019, January 8\u201314). General E(2)-equivariant steerable CNNs. Proceedings of the 33rd International Conference on Neural Information Processing Systems, Vancouver, BC, Canada. Number 1286."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Dai, J., Qi, H., Xiong, Y., Li, Y., Zhang, G., Hu, H., and Wei, Y. (2017, January 22\u201329). Deformable Convolutional Networks. Proceedings of the 2017 IEEE International Conference on Computer Vision (ICCV), Venice, Italy.","DOI":"10.1109\/ICCV.2017.89"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1007\/s11263-021-01539-8","article-title":"Semantic Edge Detection with Diverse Deep Supervision","volume":"130","author":"Liu","year":"2022","journal-title":"Int. J. Comput. Vis."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Azimi, S.M., Vig, E., Bahmanyar, R., K\u00c3\u0171rner, M., and Reinartz, P. (2018, January 2\u20136). Towards Multi-class Object Detection in Unconstrained Remote Sensing Imagery. Proceedings of the Computer Vision\u2014ACCV, Perth, Australia.","DOI":"10.1007\/978-3-030-20893-6_10"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Ding, J., Xue, N., Long, Y., Xia, G.S., and Lu, Q. (2019, January 15\u201320). Learning RoI Transformer for Oriented Object Detection in Aerial Images. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Long Beach, CA, USA.","DOI":"10.1109\/CVPR.2019.00296"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Li, C., Xu, C., Cui, Z., Wang, D., Zhang, T., and Yang, J. (2019, January 22\u201325). Feature-Attentioned Object Detection in Remote Sensing Imagery. Proceedings of the 2019 IEEE International Conference on Image Processing (ICIP), Taipei, Taiwan.","DOI":"10.1109\/ICIP.2019.8803521"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1452","DOI":"10.1109\/TPAMI.2020.2974745","article-title":"Gliding Vertex on the Horizontal Bounding Box for Multi-Oriented Object Detection","volume":"43","author":"Xu","year":"2021","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Wang, J., Ding, J., Guo, H., Cheng, W., Pan, T., and Yang, W. (2019). Mask OBB: A Semantic Attention-Based Mask Oriented Bounding Box Representation for Multi-Category Object Detection in Aerial Images. Remote Sens., 11.","DOI":"10.3390\/rs11242930"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"294","DOI":"10.1016\/j.isprsjprs.2020.01.025","article-title":"Rotation-aware and multi-scale convolutional neural network for object detection in remote sensing images","volume":"161","author":"Fu","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"4307","DOI":"10.1109\/TGRS.2020.3010051","article-title":"Learning Center Probability Map for Detecting Objects in Aerial Images","volume":"59","author":"Wang","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Chen, Z., Chen, K., Lin, W., See, J., Yu, H., Ke, Y., and Yang, C. (2020, January 23\u201328). PIoU Loss: Towards Accurate Oriented Object Detection in Complex Environments. Proceedings of the Computer Vision\u2014ECCV, Glasgow, UK.","DOI":"10.1007\/978-3-030-58558-7_12"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"223373","DOI":"10.1109\/ACCESS.2020.3041025","article-title":"Arbitrary-Oriented Object Detection in Remote Sensing Images Based on Polar Coordinates","volume":"8","author":"Zhou","year":"2020","journal-title":"IEEE Access"},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Xiao, Z., Wang, K., Wan, Q., Tan, X., Xu, C., and Xia, F. (2021). A2S-Det: Efficiency Anchor Matching in Aerial Image Oriented Object Detection. Remote Sens., 13.","DOI":"10.3390\/rs13010073"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"268","DOI":"10.1016\/j.isprsjprs.2020.09.022","article-title":"Oriented objects as pairs of middle lines","volume":"169","author":"Wei","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Pan, X., Ren, Y., Sheng, K., Dong, W., Yuan, H., Guo, X., Ma, C., and Xu, C. (2020, January 13\u201319). Dynamic Refinement Network for Oriented and Densely Packed Object Detection. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Seattle, WA, USA.","DOI":"10.1109\/CVPR42600.2020.01122"},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Yi, J., Wu, P., Liu, B., Huang, Q., Qu, H., and Metaxas, D. (2021, January 3\u20138). Oriented Object Detection in Aerial Images with Box Boundary-Aware Vectors. Proceedings of the 2021 IEEE Winter Conference on Applications of Computer Vision (WACV), Waikoloa, HI, USA.","DOI":"10.1109\/WACV48630.2021.00220"},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Zhang, S., Chi, C., Yao, Y., Lei, Z., and Li, S.Z. (2020, January 13\u201319). Bridging the Gap Between Anchor-Based and Anchor-Free Detection via Adaptive Training Sample Selection. Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, Seattle, WA, USA.","DOI":"10.1109\/CVPR42600.2020.00978"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/15\/3637\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:59:26Z","timestamp":1760140766000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/15\/3637"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,29]]},"references-count":63,"journal-issue":{"issue":"15","published-online":{"date-parts":[[2022,8]]}},"alternative-id":["rs14153637"],"URL":"https:\/\/doi.org\/10.3390\/rs14153637","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2022,7,29]]}}}