Fetching the paper…
Reading the bibliography…
In the past decade, object detection has achieved significant progress in natural images but not in aerial images, due to the massive variations in the scale and orientation of objects caused by the bird's-eye view of aerial images.
B. Yao, X. Yang, and S.-C. Zhu, “Introduction to a large-scale general purpose ground truth database: Methodology, annotation tool and benchmarks,” in
2007
Earlier work this paper cites.
C. Huang, H. Ai, Y. Li, and S. Lao, “High-performance rotation invariant multiview face detection,”
2007
Earlier work this paper cites.
G. Heitz and D. Koller, “Learning spatial context: Using stuff to find things,” in
2008
Earlier work this paper cites.
J. Deng, W. Dong, R. Socher, L. Li, K. Li, and F. Li, “Imagenet: A large-scale hierarchical image database,” in
2009
Earlier work this paper cites.
V. Reilly, H. Idrees, and M. Shah, “Detection and tracking of large number of targets in wide area surveillance,” in
2010
Earlier work this paper cites.
J. Porway, Q. Wang, and S. C. Zhu, “A hierarchical and contextual model for aerial image parsing,”
2010
Earlier work this paper cites.
M. Everingham, L. V. Gool, C. Williams, J. Winn, and A. Zisserman, “The pascal visual object classes (VOC) challenge,”
2010
Earlier work this paper cites.
J. Xiao, J. Hays, K. Ehinger, A. Oliva, and A. Torralba, “SUN database: Large-scale scene recognition from abbey to zoo,” in
2010
Earlier work this paper cites.
A. Torralba and A. A. Efros, “Unbiased look at dataset bias,” in
2011
Earlier work this paper cites.
C. Benedek, X. Descombes, and J. Zerubia, “Building development monitoring in multitemporal remotely sensed image pairs with stochastic birth-death dynamics,”
2012
Earlier work this paper cites.
T. Moranduzzo and F. Melgani, “Detecting cars in uav images with a catalog-based approach,”
2014
Earlier work this paper cites.
T. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick, “Microsoft COCO: common objects in context,” in
2014
Earlier work this paper cites.
B. Zhou, À. Lapedriza, J. Xiao, A. Torralba, and A. Oliva, “Learning deep features for scene recognition using places database,” in
2014
Earlier work this paper cites.
G. Cheng, J. Han, P. Zhou, and L. Guo, “Multi-class geospatial object detection and geographic image classification based on collection of part detectors,”
2014
Earlier work this paper cites.
R. Girshick, J. Donahue, T. Darrell, and J. Malik, “Rich feature hierarchies for accurate object detection and semantic segmentation,” in
2014
Earlier work this paper cites.
K. Liu and G. Máttyus, “Fast multiclass vehicle detection on aerial images,”
2015
Earlier work this paper cites.
H. Zhu, X. Chen, W. Dai, K. Fu, Q. Ye, and J. Jiao, “Orientation robust object detection in aerial images using deep convolutional neural network,” in
2015
Earlier work this paper cites.
R. Girshick, “Fast r-cnn,” in
2015
Earlier work this paper cites.
D. Karatzas, L. Gomez-Bigorda, A. Nicolaou, S. K. Ghosh, A. D. Bagdanov, M. Iwamura, J. Matas, L. Neumann, V. R. Chandrasekhar, S. Lu, F. Shafait, S. Uchida, and E. Valveny, “ICDAR 2015 competition on robust reading,” in
2015
Earlier work this paper cites.
Z. Liu, H. Wang, L. Weng, and Y. Yang, “Ship rotated bounding box space for ship extraction from high-resolution optical satellite images with complex backgrounds,”
2016
Earlier work this paper cites.
G. Cheng, P. Zhou, and J. Han, “Learning rotation-invariant convolutional neural networks for object detection in VHR optical remote sensing images,”
2016
Earlier work this paper cites.
S. Razakarivony and F. Jurie, “Vehicle detection in aerial imagery: A small target detection benchmark,”
2016
Earlier work this paper cites.
Q. You, J. Luo, H. Jin, and J. Yang, “Building a large scale dataset for image emotion recognition: The fine print and the benchmark,” in
2016
Earlier work this paper cites.
T. N. Mundhenk, G. Konjevod, W. A. Sakla, and K. Boakye, “A large contextual dataset for classification, detection and counting of cars with deep learning,” in
2016
Earlier work this paper cites.
W. Liu, D. Anguelov, D. Erhan, C. Szegedy, S. E. Reed, C. Fu, and A. C. Berg, “SSD: single shot multibox detector,” in
2016
Earlier work this paper cites.
S. Yang, P. Luo, C. C. Loy, and X. Tang, “WIDER FACE: A face detection benchmark,” in
2016
Earlier work this paper cites.
M.-R. Hsieh, Y.-L. Lin, and W. H. Hsu, “Drone-based object counting by spatially regularized regional proposal network,” in
2017
Earlier work this paper cites.
Y. Zhou, Q. Ye, Q. Qiu, and J. Jiao, “Oriented response networks,” in
2017
Earlier work this paper cites.
G. Xia, J. Hu, F. Hu, B. Shi, X. Bai, Y. Zhong, L. Zhang, and X. Lu, “AID: A benchmark data set for performance evaluation of aerial scene classification,”
2017
Earlier work this paper cites.
Y. Long, Y. Gong, Z. Xiao, and Q. Liu, “Accurate object localization in remote sensing images based on convolutional neural networks,”
2017
Earlier work this paper cites.
Z. Zou and Z. Shi, “Random access memories: A new paradigm for target detection in high resolution aerial remote sensing images,”
2017
Earlier work this paper cites.
J. Redmon and A. Farhadi, “Yolo9000: better, faster, stronger,” in
2017
Cited alongside, same era.
S. Ren, K. He, R. B. Girshick, and J. Sun, “Faster R-CNN: towards real-time object detection with region proposal networks,”
2017
Cited alongside, same era.
J. Dai, H. Qi, Y. Xiong, Y. Li, G. Zhang, H. Hu, and Y. Wei, “Deformable convolutional networks,”
2017
Cited alongside, same era.
Z. Liu, J. Hu, L. Weng, and Y. Yang, “Rotated region based cnn for ship detection,” in
2017
Cited alongside, same era.
T.-Y. Lin, P. Dollár, R. B. Girshick, K. He, B. Hariharan, and S. J. Belongie, “Feature pyramid networks for object detection.” in
2017
Cited alongside, same era.
J. Ding, N. Xue, Y. Long, G.-S. Xia, and Q. Lu, “Learning roi transformer for oriented object detection in aerial images,” in
2019
Later among the works it cites.
J. Pang, C. Li, J. Shi, Z. Xu, and H. Feng, “R
2019
Later among the works it cites.
F. Yang, H. Fan, P. Chu, E. Blasch, and H. Ling, “Clustered object detection in aerial images,” in
2019
Later among the works it cites.
X. Yang, J. Yang, J. Yan, Y. Zhang, T. Zhang, Z. Guo, X. Sun, and K. Fu, “Scrdet: Towards more robust detection for small, cluttered and rotated objects,” in
2019
Later among the works it cites.
C. Li, C. Xu, Z. Cui, D. Wang, Z. Jie, T. Zhang, and J. Yang, “Learning object-wise semantic representation for detection in remote sensing imagery,” in
2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
J. Huang, V. Rathod, C. Sun, M. Zhu, A. Korattikara, A. Fathi, I. Fischer, Z. Wojna, Y. Song, S. Guadarrama
2017
Cited alongside, same era.
A.-M. de Oca, R. Bahmanyar, N. Nistor, and M. Datcu, “Earth observation image semantic bias: A collaborative user annotation approach,”
2017
Cited alongside, same era.
R. Krishna, Y. Zhu, O. Groth, J. Johnson, K. Hata, J. Kravitz, S. Chen, Y. Kalantidis, L.-J. Li, D. A. Shamma
2017
Cited alongside, same era.
D. P. Papadopoulos, J. R. Uijlings, F. Keller, and V. Ferrari, “Extreme clicking for efficient object annotation,” in
2017
Cited alongside, same era.
T.-Y. Lin, P. Goyal, R. Girshick, K. He, and P. Dollár, “Focal loss for dense object detection,” in
2017
Cited alongside, same era.
K. He, G. Gkioxari, P. Dollár, and R. Girshick, “Mask r-cnn,” in
2017
Cited alongside, same era.
2017
Cited alongside, same era.
2019
Later among the works it cites.
X. Wang, Z. Cai, D. Gao, and N. Vasconcelos, “Towards universal object detection by domain attention,” in
2019
Later among the works it cites.
N. Weir, D. Lindenbaum, A. Bastidas, A. V. Etten, S. McPherson, J. Shermeyer, V. Kumar, and H. Tang, “Spacenet mvoi: A multi-view overhead imagery dataset,” in
2019
Later among the works it cites.
M. Y. Yang, W. Liao, X. Li, Y. Cao, and B. Rosenhahn, “Vehicle detection in aerial images,”
2019
Later among the works it cites.
Y. Zhang, Y. Yuan, Y. Feng, and X. Lu, “Hierarchical and robust convolutional neural network for very high-resolution remote sensing object detection,”
2019
Later among the works it cites.
S. Waqas Zamir, A. Arora, A. Gupta, S. Khan, G. Sun, F. Shahbaz Khan, F. Zhu, L. Shao, G.-S. Xia, and X. Bai, “isaid: A large-scale dataset for instance segmentation in aerial images,” in
2019
Later among the works it cites.
J. Wang, J. Ding, H. Guo, W. Cheng, T. Pan, and W. Yang, “Mask obb: A semantic attention-based mask oriented bounding box representation for multi-category object detection in aerial images,”
2019
Later among the works it cites.
Y. Wu, A. Kirillov, F. Massa, W.-Y. Lo, and R. Girshick, “Detectron2,”
2019
Later among the works it cites.
Y. Chen, C. Han, Y. Li, Z. Huang, Y. Jiang, N. Wang, and Z. Zhang, “Simpledet: A simple and versatile distributed framework for object detection and instance recognition,”
2019
Later among the works it cites.
Z. Zhang, G. Vosselman, M. Gerke, C. Persello, D. Tuia, and M. Y. Yang, “Detecting building changes between airborne laser scanning and photogrammetric data,”
2019
Later among the works it cites.
Y. He, C. Zhu, J. Wang, M. Savvides, and X. Zhang, “Bounding box regression with uncertainty for accurate object detection,” in
2019
Later among the works it cites.
K. Chen, J. Pang, J. Wang, Y. Xiong, X. Li, S. Sun, W. Feng, Z. Liu, J. Shi, W. Ouyang
2019
Later among the works it cites.
2019
Later among the works it cites.
2020
Later among the works it cites.
2020
Later among the works it cites.
K. Li, G. Wan, G. Cheng, L. Meng, and J. Han, “Object detection in optical remote sensing images: A survey and a new benchmark,”
2020
Later among the works it cites.
J. Han, J. Ding, J. Li, and G.-S. Xia, “Align deep features for oriented object detection,”
2020
Later among the works it cites.
Y. Xu, M. Fu, Q. Wang, Y. Wang, K. Chen, G.-S. Xia, and X. Bai, “Gliding vertex on the horizontal bounding box for multi-oriented object detection,”
2020
Later among the works it cites.
X. Yang and J. Yan, “Arbitrary-oriented object detection with circular smooth label,”
2020
Later among the works it cites.
J. Wang, W. Yang, H.-C. Li, H. Zhang, and G.-S. Xia, “Learning center probability map for detecting objects in aerial images,”
2020
Later among the works it cites.
B. Uzkent, C. Yeh, and S. Ermon, “Efficient object detection in large images using deep reinforcement learning,” in
2020
Later among the works it cites.
H. Zhang, F. Chen, Z. Shen, Q. Hao, C. Zhu, and M. Savvides, “Solving missing-annotation object detection with background recalibration loss,” in
2020
Later among the works it cites.
X. Pan, Y. Ren, K. Sheng, W. Dong, H. Yuan, X. Guo, C. Ma, and C. Xu, “Dynamic refinement network for oriented and densely packed object detection,” in
2020
Later among the works it cites.
X. Yang and J. Yan, “Arbitrary-oriented object detection with circular smooth label,”
2020
Later among the works it cites.
W. Li, W. Wei, and L. Zhang, “Gsdet: Object detection in aerial images based on scale reasoning,”
2021
Closest in time.