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Evan Shelhamer
Evan Shelhamer
DeepMind
Adresse e-mail validée de deepmind.com - Page d'accueil
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Année
Fully convolutional networks for semantic segmentation
J Long, E Shelhamer, T Darrell
Proceedings of the IEEE conference on computer vision and pattern …, 2015
406322015
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
176292014
cudnn: Efficient primitives for deep learning
S Chetlur, C Woolley, P Vandermersch, J Cohen, J Tran, B Catanzaro, ...
arXiv preprint arXiv:1410.0759, 2014
19822014
Deep layer aggregation
F Yu, D Wang, E Shelhamer, T Darrell
CVPR, 2018
11842018
Tent: Fully Test-Time Adaptation by Entropy Minimization
D Wang, E Shelhamer, S Liu, B Olshausen, T Darrell
ICLR, 2021
3652021
Fully convolutional multi-class multiple instance learning
D Pathak, E Shelhamer, J Long, T Darrell
arXiv preprint arXiv:1412.7144, 2014
3562014
Zero-shot visual imitation
D Pathak, P Mahmoudieh, G Luo, P Agrawal, D Chen, Y Shentu, ...
ICLR, 2018
2612018
Perceiver io: A general architecture for structured inputs & outputs
A Jaegle, S Borgeaud, JB Alayrac, C Doersch, C Ionescu, D Ding, ...
ICLR, 2021
2402021
Infinite Mixture Prototypes for Few-Shot Learning
KR Allen, E Shelhamer, H Shin, JB Tenenbaum
ICML, 232--241, 2019
2302019
Clockwork convnets for video semantic segmentation
E Shelhamer, K Rakelly, J Hoffman, T Darrell
European Conference on Computer Vision Workshops, 852-868, 2016
2242016
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
1892016
Conditional networks for few-shot semantic segmentation
K Rakelly, E Shelhamer, T Darrell, A Efros, S Levine
1782018
Loss is its own reward: Self-supervision for reinforcement learning
E Shelhamer, P Mahmoudieh, M Argus, T Darrell
arXiv preprint arXiv:1612.07307, 2016
1612016
Few-shot segmentation propagation with guided networks
K Rakelly, E Shelhamer, T Darrell, AA Efros, S Levine
arXiv preprint arXiv:1806.07373, 2018
1072018
Fine-grained pose prediction, normalization, and recognition
N Zhang, E Shelhamer, Y Gao, T Darrell
arXiv preprint arXiv:1511.07063, 2015
762015
Scene intrinsics and depth from a single image
E Shelhamer, JT Barron, T Darrell
Proceedings of the IEEE International Conference on Computer Vision …, 2015
562015
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
282019
Object discovery and representation networks
OJ Hénaff, S Koppula, E Shelhamer, D Zoran, A Jaegle, A Zisserman, ...
ECCV, 2022
272022
Evaluating the Adversarial Robustness of Adaptive Test-time Defenses
F Croce, S Gowal, T Brunner, E Shelhamer, M Hein, T Cemgil
ICML, 2022
262022
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
172021
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