David Eigen
David Eigen
Unknown affiliation
Verified email at deigen.net
Title
Cited by
Cited by
Year
Overfeat: Integrated recognition, localization and detection using convolutional networks
P Sermanet, D Eigen, X Zhang, M Mathieu, R Fergus, Y LeCun
arXiv preprint arXiv:1312.6229, 2013
50062013
Depth map prediction from a single image using a multi-scale deep network
D Eigen, C Puhrsch, R Fergus
arXiv preprint arXiv:1406.2283, 2014
25052014
Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture
D Eigen, R Fergus
Proceedings of the IEEE international conference on computer vision, 2650-2658, 2015
21712015
Restoring an image taken through a window covered with dirt or rain
D Eigen, D Krishnan, R Fergus
Proceedings of the IEEE international conference on computer vision, 633-640, 2013
3992013
Finding task-relevant features for few-shot learning by category traversal
H Li, D Eigen, S Dodge, M Zeiler, X Wang
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
1572019
Understanding deep architectures using a recursive convolutional network
D Eigen, J Rolfe, R Fergus, Y LeCun
arXiv preprint arXiv:1312.1847, 2013
1452013
Learning factored representations in a deep mixture of experts
D Eigen, MA Ranzato, I Sutskever
arXiv preprint arXiv:1312.4314, 2013
1342013
Unsupervised learning of spatiotemporally coherent metrics
R Goroshin, J Bruna, J Tompson, D Eigen, Y LeCun
Proceedings of the IEEE international conference on computer vision, 4086-4093, 2015
1252015
Nonparametric image parsing using adaptive neighbor sets
D Eigen, R Fergus
2012 IEEE Conference on Computer Vision and Pattern Recognition, 2799-2806, 2012
1052012
End-to-end integration of a convolution network, deformable parts model and non-maximum suppression
L Wan, D Eigen, R Fergus
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015
922015
Overfeat: Integrated recognition, localization and detection using convolutional networks. arXiv 2013
P Sermanet, D Eigen, X Zhang, M Mathieu, R Fergus, Y LeCun
arXiv preprint arXiv:1312.6229, 0
90
Unsupervised feature learning from temporal data
R Goroshin, J Bruna, J Tompson, D Eigen, Y LeCun
arXiv preprint arXiv:1504.02518, 2015
442015
Method and apparatus for generating dynamic microcores
DJ Eigen, DA Grunwald
US Patent 7,783,932, 2010
132010
System, method and computer-accessible medium for restoring an image taken through a window
R Fergus, D Eigen, D Krishnan
US Patent 9,373,160, 2016
102016
Overfeat: Integrated recognition, localization and detection using convolutional networks
M Mathieu, Y LeCun, R Fergus, D Eigen, P Sermanet, X Zhang
92013
Gradient agreement as an optimization objective for meta-learning
AE Eshratifar, D Eigen, M Pedram
arXiv preprint arXiv:1810.08178, 2018
62018
System and method for facilitating logo-recognition training of a recognition model
DJ Eigen, M Zeiler
US Patent 10,163,043, 2018
52018
Prediction-model-based mapping and/or search using a multi-data-type vector space
M Zeiler, D Eigen, R Compton, C Fox
US Patent App. 15/717,133, 2018
52018
A meta-learning approach for custom model training
AE Eshratifar, MS Abrishami, D Eigen, M Pedram
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 9937-9938, 2019
42019
Coarse2Fine: a two-stage training method for fine-grained visual classification
AE Eshratifar, D Eigen, M Gormish, M Pedram
Machine Vision and Applications 32 (2), 1-9, 2021
32021
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