Nathan Silberman
Nathan Silberman
Butterfly Network
Verified email at - Homepage
Cited by
Cited by
Indoor segmentation and support inference from rgbd images
N Silberman, D Hoiem, P Kohli, R Fergus
European conference on computer vision, 746-760, 2012
Unsupervised pixel-level domain adaptation with generative adversarial networks
K Bousmalis, N Silberman, D Dohan, D Erhan, D Krishnan
Proceedings of the IEEE conference on computer vision and pattern …, 2017
Domain separation networks
K Bousmalis, G Trigeorgis, N Silberman, D Krishnan, D Erhan
Advances in neural information processing systems, 343-351, 2016
Indoor scene segmentation using a structured light sensor
N Silberman, R Fergus
2011 IEEE international conference on computer vision workshops (ICCV …, 2011
Efficient large-scale distributed training of conditional maximum entropy models
R Mcdonald, M Mohri, N Silberman, D Walker, GS Mann
Advances in neural information processing systems, 1231-1239, 2009
Im2Calories: towards an automated mobile vision food diary
A Meyers, N Johnston, V Rathod, A Korattikara, A Gorban, N Silberman, ...
Proceedings of the IEEE International Conference on Computer Vision, 1233-1241, 2015
Instance segmentation of indoor scenes using a coverage loss
N Silberman, D Sontag, R Fergus
European Conference on Computer Vision, 616-631, 2014
Case for automated detection of diabetic retinopathy
N Silberman, K Ahrlich, R Fergus, L Subramanian
2010 AAAI Spring Symposium Series, 2010
Contour completion for augmenting surface reconstructions
L Shapira, R Gal, E Ofek, P Kohli, N Silberman
US Patent 9,171,403, 2015
A contour completion model for augmenting surface reconstructions
N Silberman, L Shapira, R Gal, P Kohli
European Conference on Computer Vision, 488-503, 2014
The Devil is in the Decoder.
Z Wojna, JRR Uijlings, S Guadarrama, N Silberman, LC Chen, A Fathi, ...
BMVC, 2017
The devil is in the decoder: Classification, regression and gans
Z Wojna, V Ferrari, S Guadarrama, N Silberman, LC Chen, A Fathi, ...
International Journal of Computer Vision 127 (11-12), 1694-1706, 2019
Learning from noisy labels by regularized estimation of annotator confusion
R Tanno, A Saeedi, S Sankaranarayanan, DC Alexander, N Silberman
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019
On the rise and fall of ISPs
A Sharma, N Silberman, L Subramanian, N Economides
Proceedings of Netecon 09: Workshop on the Economics of Networks, Systems …, 2009
Methods and apparatuses for identifying gestures based on ultrasound data
JM Rothberg, TS Ralston, N Silberman
US Patent App. 16/229,765, 2019
ExplainGAN: Model Explanation via Decision Boundary Crossing Transformations
P Samangouei, A Saeedi, L Nakagawa, N Silberman
Proceedings of the European Conference on Computer Vision (ECCV), 666-681, 2018
TF-Slim: A lightweight library for defining, training and evaluating complex models in TensorFlow
N Silberman
Georgia Institute of Technology, 2017
N Silberman, R Fergus, D Sontag
Transforming source domain images into target domain images
K Bousmalis, N Silberman, DM Dohan, D Erhan, D Krishnan
US Patent App. 16/442,365, 2019
Methods and apparatuses for generating and displaying ultrasound images using an explaining model
N Silberman, P Samangouei
US Patent App. 16/352,424, 2019
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