暂无分享,去创建一个
[1] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[2] Ross B. Girshick,et al. Fast R-CNN , 2015, 1504.08083.
[3] C. Lawrence Zitnick,et al. Finding the weakest link in person detectors , 2011, CVPR 2011.
[4] Jordi Pont-Tuset,et al. The Open Images Dataset V4 , 2018, International Journal of Computer Vision.
[5] Ohad Ben-Shahar,et al. Exploring the Bounds of the Utility of Context for Object Detection , 2017, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[6] Luc Van Gool,et al. The Pascal Visual Object Classes Challenge: A Retrospective , 2014, International Journal of Computer Vision.
[7] Silvio Savarese,et al. Generalized Intersection Over Union: A Metric and a Loss for Bounding Box Regression , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[8] Sergio Guadarrama,et al. Speed/Accuracy Trade-Offs for Modern Convolutional Object Detectors , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[9] Quoc V. Le,et al. EfficientDet: Scalable and Efficient Object Detection , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[10] Gustavo Carneiro,et al. Probabilistic Object Detection: Definition and Evaluation , 2020, 2020 IEEE Winter Conference on Applications of Computer Vision (WACV).
[11] Sebastian Ramos,et al. The Cityscapes Dataset for Semantic Urban Scene Understanding , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[12] Larry S. Davis,et al. An Analysis of Pre-Training on Object Detection , 2019, ArXiv.
[13] Zhe Chen,et al. Context Refinement for Object Detection , 2018, ECCV.
[14] Nicolas Pugeault,et al. Contextual Relabelling of Detected Objects , 2019, 2019 Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob).
[15] Serge J. Belongie,et al. Context based object categorization: A critical survey , 2010, Comput. Vis. Image Underst..
[16] Alexander S. Ecker,et al. Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming , 2019, ArXiv.
[17] Laurent Itti,et al. Influence of the amount of context learned for improving object classification when simultaneously learning object and contextual cues , 2012 .
[18] Pietro Perona,et al. Pedestrian Detection: An Evaluation of the State of the Art , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[19] Yongchao Gong,et al. Mask Scoring R-CNN , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[20] Ali Borji,et al. Salient Object Detection: A Benchmark , 2015, IEEE Transactions on Image Processing.
[21] Derek Hoiem,et al. Diagnosing Error in Object Detectors , 2012, ECCV.
[22] Alexei A. Efros,et al. An empirical study of context in object detection , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[23] Daphne Koller,et al. Learning Spatial Context: Using Stuff to Find Things , 2008, ECCV.
[24] Antonio Torralba,et al. Statistical Context Priming for Object Detection , 2001, ICCV.
[25] Peter I. Corke,et al. Probability-based Detection Quality (PDQ): A Probabilistic Approach to Detection Evaluation , 2018, ArXiv.
[26] Kaiming He,et al. Focal Loss for Dense Object Detection , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[27] Andrea Vedaldi,et al. Objects in Context , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[28] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[29] B. Schiele,et al. How Far are We from Solving Pedestrian Detection? , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[30] Ali Farhadi,et al. Predicting Failures of Vision Systems , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[31] Hao Chen,et al. FCOS: Fully Convolutional One-Stage Object Detection , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[32] Fei-Fei Li,et al. Detecting Avocados to Zucchinis: What Have We Done, and Where Are We Going? , 2013, 2013 IEEE International Conference on Computer Vision.
[33] John K. Tsotsos,et al. Elephant in the room , 2018 .
[34] Yair Weiss,et al. Why do deep convolutional networks generalize so poorly to small image transformations? , 2018, J. Mach. Learn. Res..
[35] M. Bar. Visual objects in context , 2004, Nature Reviews Neuroscience.
[36] Luc Van Gool,et al. The Pascal Visual Object Classes (VOC) Challenge , 2010, International Journal of Computer Vision.
[37] Kaiming He,et al. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[38] Nuno Vasconcelos,et al. Cascade R-CNN: Delving Into High Quality Object Detection , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[39] Kai Chen,et al. Hybrid Task Cascade for Instance Segmentation , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[40] Kai Chen,et al. MMDetection: Open MMLab Detection Toolbox and Benchmark , 2019, ArXiv.
[41] Stephen Lin,et al. An Empirical Study of Spatial Attention Mechanisms in Deep Networks , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[42] Wei Liu,et al. SSD: Single Shot MultiBox Detector , 2015, ECCV.
[43] Huajun Feng,et al. Libra R-CNN: Towards Balanced Learning for Object Detection , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[44] Jiri Matas,et al. Systematic evaluation of convolution neural network advances on the Imagenet , 2017, Comput. Vis. Image Underst..
[45] Jian Dong,et al. Contextualizing Object Detection and Classification , 2015, IEEE Trans. Pattern Anal. Mach. Intell..
[46] Ali Borji,et al. Quantitative Analysis of Human-Model Agreement in Visual Saliency Modeling: A Comparative Study , 2013, IEEE Transactions on Image Processing.
[47] Jieping Ye,et al. Object Detection in 20 Years: A Survey , 2019, Proceedings of the IEEE.
[48] Junjie Yan,et al. Grid R-CNN , 2018, 1811.12030.
[49] David A. Williams. The Elephant in the Room , 2011 .
[50] Sanja Fidler,et al. Human-Machine CRFs for Identifying Bottlenecks in Scene Understanding , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[51] Benjamin Recht,et al. Do ImageNet Classifiers Generalize to ImageNet? , 2019, ICML.
[52] Xingyi Zhou,et al. Objects as Points , 2019, ArXiv.
[53] Lior Wolf,et al. A Critical View of Context , 2006, International Journal of Computer Vision.
[54] Kaiming He,et al. Mask R-CNN , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[55] Ali Borji,et al. State-of-the-Art in Visual Attention Modeling , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[56] Sinan Kalkan,et al. Localization Recall Precision (LRP): A New Performance Metric for Object Detection , 2018, ECCV.
[57] Gang Sun,et al. Gather-Excite: Exploiting Feature Context in Convolutional Neural Networks , 2018, NeurIPS.
[58] Charless C. Fowlkes,et al. Do We Need More Training Data or Better Models for Object Detection? , 2012, BMVC.
[59] Antonio Torralba,et al. HOGgles: Visualizing Object Detection Features , 2013, 2013 IEEE International Conference on Computer Vision.
[60] Pietro Perona,et al. Microsoft COCO: Common Objects in Context , 2014, ECCV.