no code implementations • 6 Jan 2019 • Ryen Krusinga, Sohil Shah, Matthias Zwicker, Tom Goldstein, David Jacobs
Probability density estimation is a classical and well studied problem, but standard density estimation methods have historically lacked the power to model complex and high-dimensional image distributions.
1 code implementation • 27 Apr 2018 • Sohil Shah, Pallabi Ghosh, Larry S. Davis, Tom Goldstein
Many imaging tasks require global information about all pixels in an image.
1 code implementation • ICLR 2018 • Abhay Yadav, Sohil Shah, Zheng Xu, David Jacobs, Tom Goldstein
Adversarial neural networks solve many important problems in data science, but are notoriously difficult to train.
no code implementations • 12 Jul 2016 • Sohil Shah, Kuldeep Kulkarni, Arijit Biswas, Ankit Gandhi, Om Deshmukh, Larry Davis
Typical textual descriptions that accompany online videos are 'weak': i. e., they mention the main concepts in the video but not their corresponding spatio-temporal locations.
1 code implementation • 31 May 2016 • Sohil Shah, Abhay Kumar, Carlos Castillo, David Jacobs, Christoph Studer, Tom Goldstein
We propose a general framework to approximately solve large-scale semidefinite problems (SDPs) at low complexity.
no code implementations • CVPR 2016 • Sohil Shah, Tom Goldstein, Christoph Studer
We demonstrate the efficacy of our regularizers on a variety of imaging tasks including compressive image recovery, image restoration, and robust PCA.