Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition

Artículos que citan Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition

Título / Autor	Año
Deep residual learning for image recognition K He, X Zhang, S Ren, J Sun Proceedings of the IEEE conference on computer vision and pattern …	2016
Very deep convolutional networks for large-scale image recognition K Simonyan, A Zisserman arXiv preprint arXiv:1409.1556	2014
Imagenet large scale visual recognition challenge O Russakovsky, J Deng, H Su, J Krause, S Satheesh, S Ma, Z Huang, ... International journal of computer vision 115 (3), 211-252	2015
Faster r-cnn: Towards real-time object detection with region proposal networks S Ren, K He, R Girshick, J Sun Advances in neural information processing systems, 91-99	2015
Fully convolutional networks for semantic segmentation J Long, E Shelhamer, T Darrell Proceedings of the IEEE conference on computer vision and pattern …	2015
Fast r-cnn R Girshick Proceedings of the IEEE international conference on computer vision, 1440-1448	2015
Delving deep into rectifiers: Surpassing human-level performance on imagenet classification K He, X Zhang, S Ren, J Sun Proceedings of the IEEE international conference on computer vision, 1026-1034	2015
You only look once: Unified, real-time object detection J Redmon, S Divvala, R Girshick, A Farhadi Proceedings of the IEEE conference on computer vision and pattern …	2016
Ssd: Single shot multibox detector W Liu, D Anguelov, D Erhan, C Szegedy, S Reed, CY Fu, AC Berg European conference on computer vision, 21-37	2016
Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs LC Chen, G Papandreou, I Kokkinos, K Murphy, AL Yuille IEEE transactions on pattern analysis and machine intelligence 40 (4), 834-848	2017
Mask r-cnn K He, G Gkioxari, P Dollár, R Girshick Proceedings of the IEEE international conference on computer vision, 2961-2969	2017
Return of the devil in the details: Delving deep into convolutional nets K Chatfield, K Simonyan, A Vedaldi, A Zisserman arXiv preprint arXiv:1405.3531	2014
Image super-resolution using deep convolutional networks C Dong, CC Loy, K He, X Tang IEEE transactions on pattern analysis and machine intelligence 38 (2), 295-307	2015
Deep learning face attributes in the wild Z Liu, P Luo, X Wang, X Tang Proceedings of the IEEE international conference on computer vision, 3730-3738	2015
R-fcn: Object detection via region-based fully convolutional networks J Dai, Y Li, K He, J Sun Advances in neural information processing systems, 379-387	2016
Feature pyramid networks for object detection TY Lin, P Dollár, R Girshick, K He, B Hariharan, S Belongie Proceedings of the IEEE conference on computer vision and pattern …	2017
Pyramid scene parsing network H Zhao, J Shi, X Qi, X Wang, J Jia Proceedings of the IEEE conference on computer vision and pattern …	2017
Deep convolutional neural networks for computer-aided detection: CNN architectures, dataset characteristics and transfer learning HC Shin, HR Roth, M Gao, L Lu, Z Xu, I Nogues, J Yao, D Mollura, ... IEEE transactions on medical imaging 35 (5), 1285-1298	2016
Focal loss for dense object detection TY Lin, P Goyal, R Girshick, K He, P Dollár Proceedings of the IEEE international conference on computer vision, 2980-2988	2017
Hypercolumns for object segmentation and fine-grained localization B Hariharan, P Arbeláez, R Girshick, J Malik Proceedings of the IEEE conference on computer vision and pattern …	2015

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