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Learning Visual Representations for Transfer Learning by Suppressing Texture

Nov 04, 2020
Shlok Mishra, Anshul Shah, Ankan Bansal, Jonghyun Choi, Abhinav Shrivastava, Abhishek Sharma, David Jacobs


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On the Similarity between the Laplace and Neural Tangent Kernels

Jul 03, 2020
Amnon Geifman, Abhay Yadav, Yoni Kasten, Meirav Galun, David Jacobs, Ronen Basri


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SharinGAN: Combining Synthetic and Real Data for Unsupervised Geometry Estimation

Jun 07, 2020
Koutilya PNVR, Hao Zhou, David Jacobs

* Accepted to CVPR 2020. Supplementary material added towards the end instead of a separate file. A Github link to the code is also provided in this submission 

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Towards Automatic Generation of Questions from Long Answers

Apr 15, 2020
Shlok Kumar Mishra, Pranav Goel, Abhishek Sharma, Abhyuday Jagannatha, David Jacobs, Hal Daumé III


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Frequency Bias in Neural Networks for Input of Non-Uniform Density

Mar 10, 2020
Ronen Basri, Meirav Galun, Amnon Geifman, David Jacobs, Yoni Kasten, Shira Kritchman


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The Convergence Rate of Neural Networks for Learned Functions of Different Frequencies

Jun 02, 2019
Ronen Basri, David Jacobs, Yoni Kasten, Shira Kritchman


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Adversarially robust transfer learning

May 20, 2019
Ali Shafahi, Parsa Saadatpanah, Chen Zhu, Amin Ghiasi, Christoph Studer, David Jacobs, Tom Goldstein


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Understanding the (un)interpretability of natural image distributions using generative models

Jan 06, 2019
Ryen Krusinga, Sohil Shah, Matthias Zwicker, Tom Goldstein, David Jacobs


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SfSNet: Learning Shape, Reflectance and Illuminance of Faces in the Wild

Apr 19, 2018
Soumyadip Sengupta, Angjoo Kanazawa, Carlos D. Castillo, David Jacobs

* Accepted to CVPR 2018 (Spotlight) 

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Stabilizing Adversarial Nets With Prediction Methods

Feb 08, 2018
Abhay Yadav, Sohil Shah, Zheng Xu, David Jacobs, Tom Goldstein

* Accepted at ICLR 2018 

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3D Menagerie: Modeling the 3D shape and pose of animals

Apr 12, 2017
Silvia Zuffi, Angjoo Kanazawa, David Jacobs, Michael J. Black

* Accepted at CVPR 2017 (camera ready version) 

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Big Batch SGD: Automated Inference using Adaptive Batch Sizes

Apr 06, 2017
Soham De, Abhay Yadav, David Jacobs, Tom Goldstein

* A preliminary version of this paper appears in AISTATS 2017 (International Conference on Artificial Intelligence and Statistics) 

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Biconvex Relaxation for Semidefinite Programming in Computer Vision

Aug 08, 2016
Sohil Shah, Abhay Kumar, Carlos Castillo, David Jacobs, Christoph Studer, Tom Goldstein


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Efficient Representation of Low-Dimensional Manifolds using Deep Networks

Feb 15, 2016
Ronen Basri, David Jacobs


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A Hyperelastic Two-Scale Optimization Model for Shape Matching

Jul 28, 2015
Konrad Simon, Sameer Sheorey, David Jacobs, Ronen Basri


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Locally Scale-Invariant Convolutional Neural Networks

Dec 16, 2014
Angjoo Kanazawa, Abhishek Sharma, David Jacobs

* Deep Learning and Representation Learning Workshop: NIPS 2014 

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Comparing apples to apples in the evaluation of binary coding methods

Sep 27, 2014
Mohammad Rastegari, Shobeir Fakhraei, Jonghyun Choi, David Jacobs, Larry S. Davis


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