Evan Shelhamer
Evan Shelhamer
DeepMind
Verified email at deepmind.com - Homepage
Title
Cited by
Cited by
Year
Fully Convolutional Networks for Semantic Segmentation
E Shelhamer, J Long, T Darrell
IEEE Transactions on pattern analysis and machine intelligence 39 (4), 640-651, 2016
24698*2016
Fully convolutional networks for semantic segmentation
J Long, E Shelhamer, T Darrell
Proceedings of the IEEE conference on computer vision and pattern …, 2015
245672015
Caffe: Convolutional architecture for fast feature embedding
Y Jia, E Shelhamer, J Donahue, S Karayev, J Long, R Girshick, ...
Proceedings of the 22nd ACM international conference on Multimedia, 675-678, 2014
156862014
cudnn: Efficient primitives for deep learning
S Chetlur, C Woolley, P Vandermersch, J Cohen, J Tran, B Catanzaro, ...
arXiv preprint arXiv:1410.0759, 2014
14582014
Deep layer aggregation
F Yu, D Wang, E Shelhamer, T Darrell
arXiv preprint arXiv:1707.06484, 2017
4952017
Fully convolutional multi-class multiple instance learning
D Pathak, E Shelhamer, J Long, T Darrell
arXiv preprint arXiv:1412.7144, 2014
2932014
Zero-shot visual imitation
D Pathak, P Mahmoudieh, G Luo, P Agrawal, D Chen, Y Shentu, ...
Proceedings of the IEEE conference on computer vision and pattern …, 2018
1652018
Clockwork convnets for video semantic segmentation
E Shelhamer, K Rakelly, J Hoffman, T Darrell
European Conference on Computer Vision Workshops, 852-868, 2016
1482016
Loss is its own reward: Self-supervision for reinforcement learning
E Shelhamer, P Mahmoudieh, M Argus, T Darrell
arXiv preprint arXiv:1612.07307, 2016
1012016
Infinite Mixture Prototypes for Few-Shot Learning
KR Allen, E Shelhamer, H Shin, JB Tenenbaum
ICML, 232--241, 2019
872019
Conditional networks for few-shot semantic segmentation
K Rakelly, E Shelhamer, T Darrell, A Efros, S Levine
732018
Fine-grained pose prediction, normalization, and recognition
N Zhang, E Shelhamer, Y Gao, T Darrell
arXiv preprint arXiv:1511.07063, 2015
672015
Few-shot segmentation propagation with guided networks
K Rakelly, E Shelhamer, T Darrell, AA Efros, S Levine
arXiv preprint arXiv:1806.07373, 2018
572018
Scene intrinsics and depth from a single image
E Shelhamer, JT Barron, T Darrell
Proceedings of the IEEE International Conference on Computer Vision …, 2015
382015
Tent: Fully test-time adaptation by entropy minimization
D Wang, E Shelhamer, S Liu, B Olshausen, T Darrell
International Conference on Learning Representations 4, 6, 2021
242021
Blurring the line between structure and learning to optimize and adapt receptive fields
E Shelhamer, D Wang, T Darrell
arXiv preprint arXiv:1904.11487, 2019
172019
Transferable recognition-aware image processing
Z Liu, T Zhou, HJ Wang, Z Shen, B Kang, E Shelhamer, T Darrell
arXiv preprint arXiv:1910.09185, 2019
42019
Dynamic scale inference by entropy minimization
D Wang, E Shelhamer, B Olshausen, T Darrell
arXiv preprint arXiv:1908.03182, 2019
32019
Communal cuts: sharing cuts across images
E Shelhamer, S Jegelka, T Darrell
NeurIPS Workshop on Discrete Optimization in Machine Learning, 2014
32014
Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks
D Wang, A Ju, E Shelhamer, D Wagner, T Darrell
arXiv preprint arXiv:2105.08714, 2021
12021
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