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Visual Learning and Recognition: Difference between revisions
Visual Learning and Recognition (view source)
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<ref name="kaneva2008matching">Biliana Kaneva, Josef Sivic, Antonio Torralba, Shai Avidan, William T. Freeman (2008). Matching and Predicting Street Level Images (ECCV Workshops 2008) [https://people.csail.mit.edu/biliana/papers/eccv2010/eccv_workshop_2010.pdf https://people.csail.mit.edu/biliana/papers/eccv2010/eccv_workshop_2010.pdf]</ref> | <ref name="kaneva2008matching">Biliana Kaneva, Josef Sivic, Antonio Torralba, Shai Avidan, William T. Freeman (2008). Matching and Predicting Street Level Images (ECCV Workshops 2008) [https://people.csail.mit.edu/biliana/papers/eccv2010/eccv_workshop_2010.pdf https://people.csail.mit.edu/biliana/papers/eccv2010/eccv_workshop_2010.pdf]</ref> | ||
<ref name="xie2018rethinking">Saining Xie, Chen Sun, Jonathan Huang, Zhuowen Tu, and Kevin Murphy (2018). Rethinking Spatiotemporal Feature Learning: Speed-Accuracy Trade-offs in Video Classification (ECCV 2018) [https://arxiv.org/pdf/1712.04851.pdf https://arxiv.org/pdf/1712.04851.pdf]</ref> | <ref name="xie2018rethinking">Saining Xie, Chen Sun, Jonathan Huang, Zhuowen Tu, and Kevin Murphy (2018). Rethinking Spatiotemporal Feature Learning: Speed-Accuracy Trade-offs in Video Classification (ECCV 2018) [https://arxiv.org/pdf/1712.04851.pdf https://arxiv.org/pdf/1712.04851.pdf]</ref> | ||
<ref name="huang2018densenet">Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger (2017). Densely Connected Convolutional Networks (CVPR 2017) [https://arxiv.org/pdf/1608.06993.pdf | <ref name="huang2018densenet">Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger (2017). Densely Connected Convolutional Networks (CVPR 2017) [https://arxiv.org/pdf/1608.06993.pdf Link]</ref> | ||
<ref name="krizhevsky2012alexnet">Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton (2012) ImageNet Classification with Deep Convolutional | <ref name="krizhevsky2012alexnet">Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton (2012) ImageNet Classification with Deep Convolutional | ||
Neural Networks (NIPS 2012) [https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf | Neural Networks (NIPS 2012) [https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf Link]</ref> | ||
<ref name="felzenszwalb2009dpm">Pedro F. Felzenszwalb, Ross B. Girshick, David McAllester and Deva Ramanan (2009) Object Detection with Discriminatively Trained Part Based Models [http://cs.brown.edu/people/pfelzens/papers/lsvm-pami.pdf | <ref name="felzenszwalb2009dpm">Pedro F. Felzenszwalb, Ross B. Girshick, David McAllester and Deva Ramanan (2009) Object Detection with Discriminatively Trained Part Based Models [http://cs.brown.edu/people/pfelzens/papers/lsvm-pami.pdf Link]</ref> | ||
<ref name="liu2016ssd">Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg (2016) SSD: Single Shot MultiBox Detector [https://arxiv.org/abs/1512.02325 | <ref name="liu2016ssd">Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg (2016) SSD: Single Shot MultiBox Detector [https://arxiv.org/abs/1512.02325 Link]</ref> | ||
<ref name="redmon2016yolo">Joseph Redmon, Santosh Divvala, Ross Girshick, Ali Farhadi (2016) You Only Look Once: Unified, Real-Time Object Detection [https://pjreddie.com/media/files/papers/yolo.pdf https:// | <ref name="redmon2016yolo">Joseph Redmon, Santosh Divvala, Ross Girshick, Ali Farhadi (2016) You Only Look Once: Unified, Real-Time Object Detection [https://pjreddie.com/media/files/papers/yolo.pdf Link]</ref> | ||
<ref name="shotton2009texton">Jamie Shotton John Winn Carsten Rother Antonio Criminisi (2009) TextonBoost for Image Understanding: Multi-Class Object Recognition and Segmentation by Jointly Modeling Texture, Layout, and Context. [https://www.microsoft.com/en-us/research/publication/textonboost-for-image-understanding-multi-class-object-recognition-and-segmentation-by-jointly-modeling-texture-layout-and-context/ Link] | |||
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