Fetching the paper…
Reading the bibliography…
FPN is a common component used in object detectors, it supplements multi-scale information by adjacent level features interpolation and summation.
The pascal visual object classes (voc) challenge
M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman · 2010
Earlier work this paper cites.
Rich feature hierarchies for accurate object detection and semantic segmentation
R. Girshick, J. Donahue, T. Darrell, and J. Malik · 2014
Earlier work this paper cites.
Microsoft coco: Common objects in context
T. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollar, and C. L. Zitnick · 2014
Earlier work this paper cites.
Spatial transformer networks
M. Jaderberg, K. Simonyan, A. Zisserman, and K. Kavukcuoglu · 2015
Earlier work this paper cites.
Faster r-cnn: towards real-time object detection with region proposal networks
S. Ren, K. He, R. Girshick, and J. Sun · 2015
Earlier work this paper cites.
Fast r-cnn
G. Ross · 2015
Earlier work this paper cites.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Earlier work this paper cites.
Ssd: Single shot multibox detector
W. Liu, D. Anguelov, D. Erhan, C. Szegedy, S. Reed, C. Fu, and A. C. Berg · 2016
Earlier work this paper cites.
You only look once: Unified, real-time object detection
J. Redmon, S. K. Divvala, R. Girshick, and A. Farhadi · 2016
Earlier work this paper cites.
Sca-cnn: Spatial and channel-wise attention in convolutional networks for image captioning
L. Chen, H. Zhang, J. Xiao, L. Nie, J. Shao, W. Liu, and T. Chua · 2017
Earlier work this paper cites.
Deformable convolutional networks
J. Dai, H. Qi, Y. Xiong, Y. Li, G. Zhang, H. Hu, and Y. Wei · 2017
Earlier work this paper cites.
Mask r-cnn
K. He, G. Gkioxari, P. Dollar, and R. Girshick · 2017
Earlier work this paper cites.
Flownet 2.0: Evolution of optical flow estimation with deep networks
E. Ilg, N. Mayer, T. Saikia, M. Keuper, A. Dosovitskiy, and T. Brox · 2017
Earlier work this paper cites.
Feature pyramid networks for object detection
T. Lin, P. Dollar, R. Girshick, K. He, B. Hariharan, and S. Belongie · 2017
Earlier work this paper cites.
Focal loss for dense object detection
T. Lin, P. Goyal, R. Girshick, K. He, and P. Dollar · 2017
Earlier work this paper cites.
Pyramid scene parsing network
H. Zhao, J. Shi, X. Qi, X. Wang, and J. Jia · 2017
Earlier work this paper cites.
Cascade r-cnn: Delving into high quality object detection
Z. Cai and N. Vasconcelos · 2018
Earlier work this paper cites.
Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs
L. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille · 2018
Cited alongside, same era.
Cornernet: Detecting objects as paired keypoints
H. Law and J. Deng · 2018
Cited alongside, same era.
Pyramid attention network for semantic segmentation
H. Li, P. Xiong, J. An, and L. Wang · 2018
Cited alongside, same era.
Path aggregation network for instance segmentation
S. Liu, L. Qi, H. Qin, J. Shi, and J. Jia · 2018
Cited alongside, same era.
Yolov3: An incremental improvement
J. Redmon and A. Farhadi · 2018
Cited alongside, same era.
Non-local neural networks
X. Wang, R. Girshick, A. Gupta, and K. He · 2018
Cited alongside, same era.
Libra r-cnn: Towards balanced learning for object detection
J. Pang, K. Chen, J. Shi, H. Feng, W. Ouyang, and D. Lin · 2019
Later among the works it cites.
Thundernet: Towards real-time generic object detection on mobile devices
Z. Qin, Z. Li, Z. Zhang, Y. Bao, G. Yu, Y. Peng, and J. Sun · 2019
Later among the works it cites.
Deep high-resolution representation learning for human pose estimation
K. Sun, B. Xiao, D. Liu, and J. Wang · 2019
Later among the works it cites.
Fcos: Fully convolutional one-stage object detection
Z. Tian, C. Shen, H. Chen, and T. He · 2019
Later among the works it cites.
Carafe: Content-aware reassembly of features
J. Wang, K. Chen, R. Xu, Z. Liu, C. C. Loy, and D. Lin · 2019
Later among the works it cites.
Auto-fpn: Automatic network architecture adaptation for object detection beyond classification
H. Xu, L. Yao, Z. Li, X. Liang, and W. Zhang · 2019
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Denseaspp for semantic segmentation in street scenes
M. Yang, K. Yu, C. Zhang, Z. Li, and K. Yang · 2018
Cited alongside, same era.
Context encoding for semantic segmentation
H. Zhang, K. J. Dana, J. Shi, Z. Zhang, X. Wang, A. Tyagi, and A. Agrawal · 2018
Cited alongside, same era.
Yolact: Real-time instance segmentation
D. Bolya, C. Zhou, F. Xiao, and Y. J. Lee · 2019
Cited alongside, same era.
Mmdetection: Open mmlab detection toolbox and benchmark
K. Chen, J. Wang, J. Pang, Y. Cao, Y. Xiong, X. Li, S. Sun, W. Feng, Z. Liu, J. Xu, et al · 2019
Cited alongside, same era.
Centernet: Keypoint triplets for object detection
K. Duan, S. Bai, L. Xie, H. Qi, Q. Huang, and Q. Tian · 2019
Cited alongside, same era.
Centernet: Keypoint triplets for object detection
K. Duan, S. Bai, L. Xie, H. Qi, Q. Huang, and Q. Tian · 2019
Cited alongside, same era.
Later among the works it cites.
Bottom-up object detection by grouping extreme and center points
X. Zhou, J. Zhuo, and P. Krahenbuhl · 2019
Later among the works it cites.
Attention-guided context feature pyramid network for object detection
J. Cao, Q. Chen, J. Guo, and R. Shi · 2020
Closest in time.
Feature pyramid grids
K. Chen, Y. Cao, C. C. Loy, D. Lin, and C. Feichtenhofer · 2020
Closest in time.
Deformable kernels: Adapting effective receptive fields for object deformation
H. Gao, X. Zhu, S. Lin, and J. Dai · 2020
Closest in time.
Augfpn: Improving multi-scale feature learning for object detection
C. Guo, B. Fan, Q. Zhang, S. Xiang, and C. Pan · 2020
Closest in time.
Improving semantic segmentation via decoupled body and edge supervision
X. Li, X. Li, L. Zhang, G. Cheng, J. Shi, Z. Lin, S. Tan, and Y. Tong · 2020
Closest in time.
Semantic flow for fast and accurate scene parsing
X. Li, A. You, Z. Zhu, H. Zhao, M. Yang, K. Yang, and Y. Tong · 2020
Closest in time.
Efficientdet: Scalable and efficient object detection
M. Tan, R. Pang, and Q. V. Le · 2020
Closest in time.
Scale-equalizing pyramid convolution for object detection
X. Wang, S. Zhang, Z. Yu, L. Feng, and W. Zhang · 2020
Closest in time.
Feature pyramid transformer
D. Zhang, H. Zhang, J. Tang, M. Wang, X. Hua, and Q. Sun · 2020
Closest in time.