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Evan Shelhamer
Evan Shelhamer
DeepMind
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Title
Cited by
Cited by
Year
Fully convolutional networks for semantic segmentation
J Long, E Shelhamer, T Darrell
Proceedings of the IEEE conference on computer vision and pattern …, 2015
471392015
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
181402014
cudnn: Efficient primitives for deep learning
S Chetlur, C Woolley, P Vandermersch, J Cohen, J Tran, B Catanzaro, ...
arXiv preprint arXiv:1410.0759, 2014
22232014
Deep layer aggregation
F Yu, D Wang, E Shelhamer, T Darrell
CVPR, 2018
14672018
Tent: Fully Test-Time Adaptation by Entropy Minimization
D Wang, E Shelhamer, S Liu, B Olshausen, T Darrell
ICLR, 2021
6972021
Perceiver io: A general architecture for structured inputs & outputs
A Jaegle, S Borgeaud, JB Alayrac, C Doersch, C Ionescu, D Ding, ...
ICLR, 2021
4182021
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
4032016
Fully convolutional multi-class multiple instance learning
D Pathak, E Shelhamer, J Long, T Darrell
arXiv preprint arXiv:1412.7144, 2014
3812014
Zero-shot visual imitation
D Pathak, P Mahmoudieh, G Luo, P Agrawal, D Chen, Y Shentu, ...
ICLR, 2018
2952018
Infinite Mixture Prototypes for Few-Shot Learning
KR Allen, E Shelhamer, H Shin, JB Tenenbaum
ICML, 232--241, 2019
2702019
Clockwork convnets for video semantic segmentation
E Shelhamer, K Rakelly, J Hoffman, T Darrell
European Conference on Computer Vision Workshops, 852-868, 2016
2462016
Conditional networks for few-shot semantic segmentation
K Rakelly, E Shelhamer, T Darrell, A Efros, S Levine
2142018
Loss is its own reward: Self-supervision for reinforcement learning
E Shelhamer, P Mahmoudieh, M Argus, T Darrell
arXiv preprint arXiv:1612.07307, 2016
1922016
Few-shot segmentation propagation with guided networks
K Rakelly, E Shelhamer, T Darrell, AA Efros, S Levine
arXiv preprint arXiv:1806.07373, 2018
1212018
Fine-grained pose prediction, normalization, and recognition
N Zhang, E Shelhamer, Y Gao, T Darrell
arXiv preprint arXiv:1511.07063, 2015
762015
Object discovery and representation networks
OJ Hénaff, S Koppula, E Shelhamer, D Zoran, A Jaegle, A Zisserman, ...
ECCV, 2022
612022
Scene intrinsics and depth from a single image
E Shelhamer, JT Barron, T Darrell
Proceedings of the IEEE International Conference on Computer Vision …, 2015
592015
Evaluating the Adversarial Robustness of Adaptive Test-time Defenses
F Croce, S Gowal, T Brunner, E Shelhamer, M Hein, T Cemgil
ICML, 2022
482022
Back to the Source: Diffusion-Driven Adaptation To Test-Time Corruption
J Gao, J Zhang, X Liu, T Darrell, E Shelhamer, D Wang
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
44*2023
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
322019
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