Benjamin Graham
Benjamin Graham
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Zitiert von
Zitiert von
3d semantic segmentation with submanifold sparse convolutional networks
B Graham, M Engelcke, L Van Der Maaten
Proceedings of the IEEE conference on computer vision and pattern …, 2018
Sparse 3D convolutional neural networks
B Graham
BMVC 2015, 150.1-150.9, 2015
Fractional max-pooling
B Graham
arXiv preprint arXiv:1412.6071, 2014
Levit: a vision transformer in convnet's clothing for faster inference
B Graham, A El-Nouby, H Touvron, P Stock, A Joulin, H Jégou, M Douze
Proceedings of the IEEE/CVF international conference on computer vision …, 2021
Submanifold sparse convolutional networks
B Graham, L Van der Maaten
arXiv preprint arXiv:1706.01307, 2017
Spatially-sparse convolutional neural networks
B Graham
arXiv preprint arXiv:1409.6070, 2014
Alaaeldin El-Nouby, Hugo Touvron, Pierre Stock, Armand Joulin, Hervé Jégou, and Matthijs Douze. Levit: a vision transformer in convnet’s clothing for faster inference
B Graham
arXiv preprint arXiv:2104.01136 2 (3), 5, 2021
Exploring data-efficient 3d scene understanding with contrastive scene contexts
J Hou, B Graham, M Nießner, S Xie
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
Training with quantization noise for extreme model compression
A Fan, P Stock, B Graham, E Grave, R Gribonval, H Jegou, A Joulin
arXiv preprint arXiv:2004.07320, 2020
Kaggle diabetic retinopathy detection competition report
B Graham
University of Warwick 22, 17, 2015
And the bit goes down: Revisiting the quantization of neural networks
P Stock, A Joulin, R Gribonval, B Graham, H Jégou
arXiv preprint arXiv:1907.05686, 2019
C3DPO: Canonical 3D Pose Networks for Non-Rigid Structure From Motion
AV David Novotny, Nikhila Ravi, Benjamin Graham, Natalia Neverova
ICCV, 2019
Automated plankton image analysis using convolutional neural networks
RKC Jessica Y. Luo, Jean‐Olivier Irisson, Benjamin Graham, Cedric Guigand ...
Limnology and Oceanography: Methods, 2018
Sparse arrays of signatures for online character recognition
B Graham
arXiv preprint arXiv:1308.0371, 2013
Analyzing spatially-sparse data based on submanifold sparse convolutional neural networks
BT Graham, LJP van der Maaten, MH Engelcke
US Patent 11,544,550, 2023
3d multi-bodies: Fitting sets of plausible 3d human models to ambiguous image data
B Biggs, D Novotny, S Ehrhardt, H Joo, B Graham, A Vedaldi
Advances in neural information processing systems 33, 20496-20507, 2020
Large-scale 3d shape reconstruction and segmentation from shapenet core55
L Yi, L Shao, M Savva, H Huang, Y Zhou, Q Wang, B Graham, M Engelcke, ...
arXiv preprint arXiv:1710.06104, 2017
Influence and sharp-threshold theorems for monotonic measures
BT Graham, GR Grimmett
Pri3d: Can 3d priors help 2d representation learning?
J Hou, S Xie, B Graham, A Dai, M Nießner
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
Cotracker: It is better to track together
N Karaev, I Rocco, B Graham, N Neverova, A Vedaldi, C Rupprecht
arXiv preprint arXiv:2307.07635, 2023
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