Fast Edge Detection Using Structured Forests - Estadísticas de Google Académico

Artículos que citan Fast Edge Detection Using Structured Forests

Título / Autor	Año
Edge boxes: Locating object proposals from edges CL Zitnick, P Dollár European conference on computer vision, 391-405	2014
Holistically-nested edge detection S Xie, Z Tu Proceedings of the IEEE international conference on computer vision, 1395-1403	2015
Learning rich features from RGB-D images for object detection and segmentation S Gupta, R Girshick, P Arbeláez, J Malik European conference on computer vision, 345-360	2014
Reading text in the wild with convolutional neural networks M Jaderberg, K Simonyan, A Vedaldi, A Zisserman International Journal of Computer Vision 116 (1), 1-20	2016
What makes for effective detection proposals? J Hosang, R Benenson, P Dollár, B Schiele IEEE transactions on pattern analysis and machine intelligence 38 (4), 814-830	2015
Deepcontour: A deep convolutional feature learned by positive-sharing loss for contour detection W Shen, X Wang, Y Wang, X Bai, Z Zhang Proceedings of the IEEE conference on computer vision and pattern …	2015
Deepedge: A multi-scale bifurcated deep network for top-down contour detection G Bertasius, J Shi, L Torresani Proceedings of the IEEE conference on computer vision and pattern …	2015
Convolutional channel features B Yang, J Yan, Z Lei, SZ Li Proceedings of the IEEE international conference on computer vision, 82-90	2015
Face detection with the faster R-CNN H Jiang, E Learned-Miller 2017 12th IEEE International Conference on Automatic Face & Gesture …	2017
Ubernet: Training a universal convolutional neural network for low-, mid-, and high-level vision using diverse datasets and limited memory I Kokkinos Proceedings of the IEEE Conference on Computer Vision and Pattern …	2017
Robust nucleus/cell detection and segmentation in digital pathology and microscopy images: a comprehensive review F Xing, L Yang IEEE reviews in biomedical engineering 9, 234-263	2016
Learning deep representation for imbalanced classification C Huang, Y Li, C Change Loy, X Tang Proceedings of the IEEE conference on computer vision and pattern …	2016
Richer convolutional features for edge detection Y Liu, MM Cheng, X Hu, K Wang, X Bai Proceedings of the IEEE conference on computer vision and pattern …	2017
Pushing the boundaries of boundary detection using deep learning I Kokkinos arXiv preprint arXiv:1511.07386	2015
Feature space optimization for semantic video segmentation A Kundu, V Vineet, V Koltun Proceedings of the IEEE Conference on Computer Vision and Pattern …	2016
High-for-low and low-for-high: Efficient boundary detection from deep object features and its applications to high-level vision G Bertasius, J Shi, L Torresani Proceedings of the IEEE International Conference on Computer Vision, 504-512	2015
Video propagation networks V Jampani, R Gadde, PV Gehler Proceedings of the IEEE Conference on Computer Vision and Pattern …	2017
Physically-based rendering for indoor scene understanding using convolutional neural networks Y Zhang, S Song, E Yumer, M Savva, JY Lee, H Jin, T Funkhouser Proceedings of the IEEE Conference on Computer Vision and Pattern …	2017
A review on the main challenges in automatic plant disease identification based on visible range images JGA Barbedo Biosystems engineering 144, 52-60	2016
Semantic segmentation with boundary neural fields G Bertasius, J Shi, L Torresani Proceedings of the IEEE conference on computer vision and pattern …	2016

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