Synthesizing Scenes for Instance Detection
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[1] Yoshua Bengio,et al. Extracting and composing robust features with denoising autoencoders , 2008, ICML '08.
[2] Pietro Perona,et al. Microsoft COCO: Common Objects in Context , 2014, ECCV.
[3] Luc Van Gool,et al. The Pascal Visual Object Classes Challenge: A Retrospective , 2014, International Journal of Computer Vision.
[4] Leonidas J. Guibas,et al. ShapeNet: An Information-Rich 3D Model Repository , 2015, ArXiv.
[5] Jana Kosecka,et al. Synthesizing Training Data for Object Detection in Indoor Scenes , 2017, Robotics: Science and Systems.
[6] Mathieu Aubry,et al. Deep Exemplar 2D-3D Detection by Adapting from Real to Rendered Views , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[7] 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.
[8] Ronan Sicre,et al. Particular object retrieval with integral max-pooling of CNN activations , 2015, ICLR.
[9] Jana Kosecka,et al. Multiview RGB-D Dataset for Object Instance Detection , 2016, 2016 Fourth International Conference on 3D Vision (3DV).
[10] Cordelia Schmid,et al. A Comparison of Affine Region Detectors , 2005, International Journal of Computer Vision.
[11] Matthijs C. Dorst. Distinctive Image Features from Scale-Invariant Keypoints , 2011 .
[12] Pittsburgh,et al. The MOPED framework: Object recognition and pose estimation for manipulation , 2011 .
[13] Ankush Gupta,et al. Synthetic Data for Text Localisation in Natural Images , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[14] Trevor Darrell,et al. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation , 2013, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[15] Antonio M. López,et al. The SYNTHIA Dataset: A Large Collection of Synthetic Images for Semantic Segmentation of Urban Scenes , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[16] Deva Ramanan,et al. Efficiently Scaling up Crowdsourced Video Annotation , 2012, International Journal of Computer Vision.
[17] Dieter Fox,et al. A large-scale hierarchical multi-view RGB-D object dataset , 2011, 2011 IEEE International Conference on Robotics and Automation.
[18] Kate Saenko,et al. Learning Deep Object Detectors from 3D Models , 2014, 2015 IEEE International Conference on Computer Vision (ICCV).
[19] David G. Lowe,et al. Local feature view clustering for 3D object recognition , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.
[20] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[21] Vincent Lepetit,et al. Gradient Response Maps for Real-Time Detection of Textureless Objects , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[22] Kuan-Ting Yu,et al. Multi-view self-supervised deep learning for 6D pose estimation in the Amazon Picking Challenge , 2016, 2017 IEEE International Conference on Robotics and Automation (ICRA).
[23] Silvio Savarese,et al. Beyond PASCAL: A benchmark for 3D object detection in the wild , 2014, IEEE Winter Conference on Applications of Computer Vision.
[24] Takeo Kanade,et al. How Useful Is Photo-Realistic Rendering for Visual Learning? , 2016, ECCV Workshops.
[25] Alvaro Collet,et al. Making specific features less discriminative to improve point-based 3D object recognition , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[26] Trevor Darrell,et al. Simultaneous Deep Transfer Across Domains and Tasks , 2015, ICCV.
[27] Qiao Wang,et al. VirtualWorlds as Proxy for Multi-object Tracking Analysis , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[28] Wei Liu,et al. SSD: Single Shot MultiBox Detector , 2015, ECCV.
[29] Zhenhua Wang,et al. Synthesizing Training Images for Boosting Human 3D Pose Estimation , 2016, 2016 Fourth International Conference on 3D Vision (3DV).
[30] David A. McAllester,et al. A discriminatively trained, multiscale, deformable part model , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[31] Patrick Pérez,et al. Poisson image editing , 2003, ACM Trans. Graph..
[32] Silvio Savarese,et al. Robust single-view instance recognition , 2016, 2016 IEEE International Conference on Robotics and Automation (ICRA).
[33] Thomas Brox,et al. Unsupervised Generation of a View Point Annotated Car Dataset from Videos , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[34] Deva Ramanan,et al. Articulated pose estimation with tiny synthetic videos , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[35] Bolei Zhou,et al. SegICP: Integrated deep semantic segmentation and pose estimation , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[36] Lawrence D. Jackel,et al. Backpropagation Applied to Handwritten Zip Code Recognition , 1989, Neural Computation.
[37] David A. Forsyth,et al. Rendering synthetic objects into legacy photographs , 2011, ACM Trans. Graph..
[38] Qi Tian,et al. SIFT Meets CNN: A Decade Survey of Instance Retrieval , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[39] Cordelia Schmid,et al. Learning from Synthetic Humans , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[40] Pieter Abbeel,et al. BigBIRD: A large-scale 3D database of object instances , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).
[41] Jonathan T. Barron,et al. The Fast Bilateral Solver , 2015, ECCV.
[42] Leonidas J. Guibas,et al. Render for CNN: Viewpoint Estimation in Images Using CNNs Trained with Rendered 3D Model Views , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[43] Jianxiong Xiao,et al. Robot In a Room: Toward Perfect Object Recognition in Closed Environments , 2015, ArXiv.
[44] Stefan Carlsson,et al. CNN Features Off-the-Shelf: An Astounding Baseline for Recognition , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops.
[45] Vladlen Koltun,et al. Playing for Data: Ground Truth from Computer Games , 2016, ECCV.
[46] Kostas E. Bekris,et al. A self-supervised learning system for object detection using physics simulation and multi-view pose estimation , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[47] Roberto Cipolla,et al. SceneNet: Understanding Real World Indoor Scenes With Synthetic Data , 2015, ArXiv.
[48] Jana Kosecka,et al. A dataset for developing and benchmarking active vision , 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).
[49] Luc Van Gool,et al. Speeded-Up Robust Features (SURF) , 2008, Comput. Vis. Image Underst..
[50] Derek Hoiem,et al. Diagnosing Error in Object Detectors , 2012, ECCV.
[51] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[52] Ali Farhadi,et al. You Only Look Once: Unified, Real-Time Object Detection , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[53] Luc Van Gool,et al. Object Detection by Contour Segment Networks , 2006, ECCV.