ParseNet: Looking Wider to See Better

Keywords

Pascal (unit), Computer science, Normalization (sociology), Segmentation, Artificial intelligence

References

• Understanding the difficulty of training deep feedforward neural networksXavier Glorot, Yoshua Bengio — 2010
• Scalable, High-Quality Object DetectionChristian Szegedy, Scott Reed, Dumitru Erhan — 2014
• Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet ClassificationKaiming He, Xiangyu Zhang, Shaoqing Ren — 2015
• Very Deep Convolutional Networks for Large-Scale Image RecognitionKaren Simonyan, Andrew Zisserman — 2014
• Fully convolutional networks for semantic segmentationJonathan Long, Evan Shelhamer, Trevor Darrell — 2014
• Feedforward semantic segmentation with zoom-out featuresMohammadreza Mostajabi, Payman Yadollahpour, Gregory Shakhnarovich — 2014
• Hypercolumns for object segmentation and fine-grained localizationBharath Hariharan, Pablo Arbeláez, Ross Girshick — 2014
• The Pascal Visual Object Classes Challenge: A RetrospectiveMark Everingham, S. M. Ali Eslami, Luc Van Gool — 2014
• CPMC: Automatic Object Segmentation Using Constrained Parametric Min-CutsJoão Carreira, Cristian Sminchisescu — 2012
• TextonBoost for Image Understanding: Multi-Class Object Recognition and Segmentation by Jointly Modeling Texture, Layout, and ContextJamie Shotton, John Winn, Carsten Rother — 2007
• Objects in ContextAndrew Rabinovich, Andrea Vedaldi, Carolina Galleguillos — 2007
• Selective Search for Object RecognitionJasper Uijlings, Koen E. A. van de Sande, Theo Gevers — 2013
• Going deeper with convolutionsChristian Szegedy, Wei Liu, Yangqing Jia — 2014
• Fully Connected Deep Structured NetworksAlexander G. Schwing, Raquel Urtasun — 2015
• Rich Feature Hierarchies for Accurate Object Detection and Semantic SegmentationRoss Girshick, Jeff Donahue, Trevor Darrell — 2013
• Spatial Pyramid Pooling in Deep Convolutional Networks for Visual RecognitionKaiming He, Xiangyu Zhang, Shaoqing Ren — 2014
• Robust Higher Order Potentials for Enforcing Label ConsistencyPushmeet Kohli, Ľubor Ladický, Philip H. S. Torr — 2008
• Conditional Random Fields as Recurrent Neural NetworksShuai Zheng, Sadeep Jayasumana, Bernardino Romera‐Paredes — 2015
• The Role of Context for Object Detection and Semantic Segmentation in the WildRoozbeh Mottaghi, Xianjie Chen, Xiaobai Liu — 2014
• Semantic contours from inverse detectorsBharath Hariharan, Pablo Arbeláez, Lubomir Bourdev — 2011

Cited by

• Deep Crisp Boundaries: From Boundaries to Higher-Level TasksMikel Aramendi Arteaga — 2018
• Fully convolutional networks for semantic segmentationJonathan Long, Evan Shelhamer, Trevor Darrell — 2014
• SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image SegmentationVijay Badrinarayanan, Alex Kendall, Roberto Cipolla — 2015
• DenseBox: Unifying Landmark Localization with End to End Object DetectionLichao Huang, Yi Yang, Yafeng Deng — 2015
• Attention to Scale: Scale-Aware Semantic Image SegmentationLiang-Chieh Chen, Yi Yang, Jiang Wang — 2015
• Learning High-level Prior with Convolutional Neural Networks for Semantic SegmentationHaitian Zheng, Yebin Liu, Mengqi Ji — 2015
• DOC: Deep OCclusion Recovering From A Single ImagePeng Wang, Alan Yuille — 2015
• Dense Recurrent Neural Networks for Scene LabelingBing Shuai, Zhen Zuo, Bing Wang — 2018
• Inside-Outside Net: Detecting Objects in Context with Skip Pooling and Recurrent Neural NetworksSean Bell, C. Lawrence Zitnick, Kavita Bala — 2015
• A Fully Convolutional Neural Network for Cardiac Segmentation in Short-Axis MRIPhi Vu Tran — 2016
• STD2P: RGBD Semantic Segmentation Using Spatio-Temporal Data-Driven PoolingYang He, Wei-Chen Chiu, Margret Keuper — 2016
• The Cityscapes Dataset for Semantic Urban Scene UnderstandingMarius Cordts, Mohamed Omran, Sebastian Ramos — 2016
• Higher Order Conditional Random Fields in Deep Neural NetworksAnurag Arnab, Sadeep Jayasumana, Shuai Zheng — 2015
• Fully Convolutional Networks for Semantic SegmentationEvan Shelhamer, Jonathan Long, Trevor Darrell — 2017
• DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFsLiang-Chieh Chen, George Papandreou, Iasonas Kokkinos — 2016
• Multiple Scale Faster-RCNN Approach to Driver’s Cell-Phone Usage and Hands on Steering Wheel DetectionNgan Le, Yutong Zheng, Chenchen Zhu — 2016
• Detection of small birds in large images by combining a deep detector with semantic segmentationAkito Takeki, Tu Tuan Trinh, Ryota Yoshihashi — 2016
• Multi-Path Feedback Recurrent Neural Networks for Scene ParsingXiaojie Jin, Yunpeng Chen, Jiashi Feng — 2016
• UberNet: Training a Universal Convolutional Neural Network for Low-, Mid-, and High-Level Vision Using Diverse Datasets and Limited MemoryIasonas Kokkinos — 2016
• Deeper and wider fully convolutional network coupled with conditional random fields for scene labelingKien Nguyen, Clinton Fookes, Sridha Sridharan — 2016

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