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Network Dissection: Quantifying Interpretability of Deep Visual Representations

Apr 19, 2017
David Bau, Bolei Zhou, Aditya Khosla, Aude Oliva, Antonio Torralba

* First two authors contributed equally. Oral presentation at CVPR 2017 

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Following Gaze Across Views

Dec 09, 2016
Adrià Recasens, Carl Vondrick, Aditya Khosla, Antonio Torralba

* 9 pages, 8 figures 

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Places: An Image Database for Deep Scene Understanding

Oct 06, 2016
Bolei Zhou, Aditya Khosla, Agata Lapedriza, Antonio Torralba, Aude Oliva

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Eye Tracking for Everyone

Jun 18, 2016
Kyle Krafka, Aditya Khosla, Petr Kellnhofer, Harini Kannan, Suchendra Bhandarkar, Wojciech Matusik, Antonio Torralba

* The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016 

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Deep Learning for Identifying Metastatic Breast Cancer

Jun 18, 2016
Dayong Wang, Aditya Khosla, Rishab Gargeya, Humayun Irshad, Andrew H. Beck

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Deep Neural Networks predict Hierarchical Spatio-temporal Cortical Dynamics of Human Visual Object Recognition

Jan 12, 2016
Radoslaw M. Cichy, Aditya Khosla, Dimitrios Pantazis, Antonio Torralba, Aude Oliva

* 15 pages, 6 figures 

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Learning Deep Features for Discriminative Localization

Dec 14, 2015
Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, Antonio Torralba

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Object Detectors Emerge in Deep Scene CNNs

Apr 15, 2015
Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, Antonio Torralba

* 12 pages, ICLR 2015 conference paper 

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3D ShapeNets: A Deep Representation for Volumetric Shapes

Apr 15, 2015
Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, Jianxiong Xiao

* to be appeared in CVPR 2015 

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Visualizing Object Detection Features

Feb 19, 2015
Carl Vondrick, Aditya Khosla, Hamed Pirsiavash, Tomasz Malisiewicz, Antonio Torralba

* In submission to IJCV 

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ImageNet Large Scale Visual Recognition Challenge

Jan 30, 2015
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, Li Fei-Fei

* 43 pages, 16 figures. v3 includes additional comparisons with PASCAL VOC (per-category comparisons in Table 3, distribution of localization difficulty in Fig 16), a list of queries used for obtaining object detection images (Appendix C), and some additional references 

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Inverting and Visualizing Features for Object Detection

May 05, 2013
Carl Vondrick, Aditya Khosla, Tomasz Malisiewicz, Antonio Torralba

* This paper is a preprint of our conference paper. We have made it available early in the hopes that others find it useful 

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