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Hartwig Adam
Hartwig Adam
Director of Engineering, Google Research
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
Mobilenets: Efficient convolutional neural networks for mobile vision applications
AG Howard, M Zhu, B Chen, D Kalenichenko, W Wang, T Weyand, ...
arXiv preprint arXiv:1704.04861, 2017
131182017
Encoder-decoder with atrous separable convolution for semantic image segmentation
LC Chen, Y Zhu, G Papandreou, F Schroff, H Adam
Proceedings of the European Conference on Computer Vision (ECCV), 801-818, 2018
64542018
Rethinking atrous convolution for semantic image segmentation
LC Chen, G Papandreou, F Schroff, H Adam
arXiv preprint arXiv:1706.05587, 2017
48282017
Searching for mobilenetv3
A Howard, M Sandler, G Chu, LC Chen, B Chen, M Tan, W Wang, Y Zhu, ...
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
20852019
Quantization and training of neural networks for efficient integer-arithmetic-only inference
B Jacob, S Kligys, B Chen, M Zhu, M Tang, A Howard, H Adam, ...
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
15752018
Auto-deeplab: Hierarchical neural architecture search for semantic image segmentation
C Liu, LC Chen, F Schroff, H Adam, W Hua, AL Yuille, L Fei-Fei
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
7222019
Tour the world: building a web-scale landmark recognition engine
YT Zheng, M Zhao, Y Song, H Adam, U Buddemeier, A Bissacco, ...
2009 IEEE Conference on Computer Vision and Pattern Recognition, 1085-1092, 2009
4752009
Large-scale object classification using label relation graphs
J Deng, N Ding, Y Jia, A Frome, K Murphy, S Bengio, Y Li, H Neven, ...
European conference on computer vision, 48-64, 2014
4482014
Netadapt: Platform-aware neural network adaptation for mobile applications
TJ Yang, A Howard, B Chen, X Zhang, A Go, M Sandler, V Sze, H Adam
Proceedings of the European Conference on Computer Vision (ECCV), 285-300, 2018
3992018
The inaturalist species classification and detection dataset
G Van Horn, O Mac Aodha, Y Song, Y Cui, C Sun, A Shepard, H Adam, ...
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
3742018
Searching for efficient multi-scale architectures for dense image prediction
LC Chen, M Collins, Y Zhu, G Papandreou, B Zoph, F Schroff, H Adam, ...
Advances in Neural Information Processing Systems, 8713-8724, 2018
3312018
Masklab: Instance segmentation by refining object detection with semantic and direction features
LC Chen, A Hermans, G Papandreou, F Schroff, P Wang, H Adam
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
2962018
Large-scale privacy protection in google street view
A Frome, G Cheung, A Abdulkader, M Zennaro, B Wu, A Bissacco, ...
2009 IEEE 12th international conference on computer vision, 2373-2380, 2009
2672009
MobileNets: efficient convolutional neural networks for mobile vision applications (2017)
AG Howard, M Zhu, B Chen, D Kalenichenko, W Wang, T Weyand, ...
arXiv preprint arXiv:1704.04861 126, 2017
2522017
Feelvos: Fast end-to-end embedding learning for video object segmentation
P Voigtlaender, Y Chai, F Schroff, H Adam, B Leibe, LC Chen
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
2492019
Oisin Mac Aodha, Yang Song, Yin Cui, Chen Sun, Alex Shepard, Hartwig Adam, Pietro Perona, and Serge Belongie. The inaturalist species classification and detection dataset
G Van Horn
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018
2482018
Facial recognition with social network aiding
D Petrou, A Rabinovich, H Adam
US Patent 8,670,597, 2014
2472014
Axial-deeplab: Stand-alone axial-attention for panoptic segmentation
H Wang, Y Zhu, B Green, H Adam, A Yuille, LC Chen
European Conference on Computer Vision, 108-126, 2020
2342020
Panoptic-DeepLab: A Simple, Strong, and Fast Baseline for Bottom-Up Panoptic Segmentation
B Cheng, MD Collins, Y Zhu, T Liu, TS Huang, H Adam, LC Chen
arXiv preprint arXiv:1911.10194, 2019
2212019
Image based multi-biometric system and method
H Adam, H Neven, JB Steffens
US Patent 7,697,735, 2010
2142010
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