Understanding image representations by measuring their equivariance and
equivalence

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Understanding image representations by measuring their equivariance and equivalence

21 November 2014

Andrea Vedaldi

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Papers citing "Understanding image representations by measuring their equivariance and equivalence"

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cvpaper.challenge in 2015 - A review of CVPR2015 and DeepSurvey Hirokatsu Kataoka Yudai Miyashita Tomoaki K. Yamabe Soma Shirakabe Shin-ichi Sato ... Kaori Abe Takaaki Imanari Naomichi Kobayashi Shinichiro Morita Akio Nakamura 55 2 0 26 May 2016
Comparative Deep Learning of Hybrid Representations for Image Recommendations Chenyi Lei Dong Liu Weiping Li Zhengjun Zha Houqiang Li 74 112 0 05 Apr 2016
Group Equivariant Convolutional Networks Taco S. Cohen Max Welling BDL 217 1,949 0 24 Feb 2016
Exploiting Cyclic Symmetry in Convolutional Neural Networks Sander Dieleman J. Fauw Koray Kavukcuoglu 134 364 0 08 Feb 2016
Learning scale-variant and scale-invariant features for deep image classification Nanne van Noord E. Postma SSL 80 158 0 03 Feb 2016
Deep Exemplar 2D-3D Detection by Adapting from Real to Rendered Views Francisco Massa Bryan C. Russell Mathieu Aubry 3DV ObjD 157 100 0 08 Dec 2015
Analyzing Classifiers: Fisher Vectors and Deep Neural Networks Sebastian Bach Alexander Binder G. Montavon K. Müller Wojciech Samek 87 199 0 01 Dec 2015
Cross Modal Distillation for Supervision Transfer Saurabh Gupta Judy Hoffman Jitendra Malik 136 539 0 02 Jul 2015
Slow and steady feature analysis: higher order temporal coherence in video Dinesh Jayaraman Kristen Grauman 110 143 0 15 Jun 2015
Visualizing Object Detection Features Carl Vondrick A. Khosla Hamed Pirsiavash Tomasz Malisiewicz Antonio Torralba 95 56 0 19 Feb 2015