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ORCIDJosé M. Álvarez
- > Home > Persons > José M. Álvarez
Publications
- 2023
[c23]Shuxuan Guo, Yinlin Hu, Jose M. Alvarez, Mathieu Salzmann:
Knowledge Distillation for 6D Pose Estimation by Aligning Distributions of Local Predictions. CVPR 2023: 18633-18642- 2022
- [i12]Shuxuan Guo, Yinlin Hu, Jose M. Alvarez, Mathieu Salzmann:
Knowledge Distillation for 6D Pose Estimation by Keypoint Distribution Alignment. CoRR abs/2205.14971 (2022) - 2021
- [c22]Shuxuan Guo, Jose M. Alvarez, Mathieu Salzmann:
Distilling Image Classifiers in Object Detectors. NeurIPS 2021: 1036-1047 - [i11]Shuxuan Guo, Jose M. Alvarez, Mathieu Salzmann:
Distilling Image Classifiers in Object Detectors. CoRR abs/2106.05209 (2021) - 2020
- [c21]Shuxuan Guo, Jose M. Alvarez, Mathieu Salzmann:
ExpandNets: Linear Over-parameterization to Train Compact Convolutional Networks. NeurIPS 2020 - 2018
- [i10]Shuxuan Guo, Jose M. Alvarez, Mathieu Salzmann:
ExpandNets: Exploiting Linear Redundancy to Train Small Networks. CoRR abs/1811.10495 (2018) - 2017
- [c18]Fatemehsadat Saleh, Mohammad Sadegh Ali Akbarian, Mathieu Salzmann, Lars Petersson
, Jose M. Alvarez:
Bringing Background into the Foreground: Making All Classes Equal in Weakly-Supervised Video Semantic Segmentation. ICCV 2017: 2125-2135 - [c16]Jose M. Alvarez, Mathieu Salzmann:
Compression-aware Training of Deep Networks. NIPS 2017: 856-867 - [i8]Fatemehsadat Saleh, Mohammad Sadegh Ali Akbarian, Mathieu Salzmann, Lars Petersson, Jose M. Alvarez, Stephen Gould:
Incorporating Network Built-in Priors in Weakly-supervised Semantic Segmentation. CoRR abs/1706.02189 (2017) - [i6]Fatemehsadat Saleh, Mohammad Sadegh Ali Akbarian, Mathieu Salzmann, Lars Petersson, Jose M. Alvarez:
Bringing Background into the Foreground: Making All Classes Equal in Weakly-supervised Video Semantic Segmentation. CoRR abs/1708.04400 (2017) - [i5]Jose M. Alvarez, Mathieu Salzmann:
Compression-aware Training of Deep Networks. CoRR abs/1711.02638 (2017) - 2016
- [j1]Lachlan Horne, Jose M. Alvarez, Chris McCarthy, Mathieu Salzmann, Nick Barnes:
Semantic labeling for prosthetic vision. Comput. Vis. Image Underst. 149: 113-125 (2016) - [c15]Fatemehsadat Saleh, Mohammad Sadegh Ali Akbarian, Mathieu Salzmann, Lars Petersson, Stephen Gould, Jose M. Alvarez:
Built-in Foreground/Background Prior for Weakly-Supervised Semantic Segmentation. ECCV (8) 2016: 413-432 - [c10]Jose M. Alvarez, Mathieu Salzmann:
Learning the Number of Neurons in Deep Networks. NIPS 2016: 2262-2270 - [c9]Jose M. Alvarez, Mathieu Salzmann, Nick Barnes:
Efficient transductive semantic segmentation. WACV 2016: 1-9 - [i2]Fatemehsadat Saleh, Mohammad Sadegh Ali Akbarian, Mathieu Salzmann, Lars Petersson, Stephen Gould, Jose M. Alvarez:
Built-in Foreground/Background Prior for Weakly-Supervised Semantic Segmentation. CoRR abs/1609.00446 (2016) - [i1]Jose M. Alvarez, Mathieu Salzmann:
Learning the Number of Neurons in Deep Networks. CoRR abs/1611.06321 (2016) - 2015
- [c6]Lachlan Horne, Jose M. Alvarez, Mathieu Salzmann, Nick Barnes:
Efficient scene parsing by sampling unary potentials in a fully-connected CRF. Intelligent Vehicles Symposium 2015: 820-825 - 2014
- [c4]Jose M. Alvarez, Mathieu Salzmann, Nick Barnes:
Large-scale semantic co-labeling of image sets. WACV 2014: 501-508 - [c3]Jose M. Alvarez, Mathieu Salzmann, Nick Barnes:
Data-driven road detection. WACV 2014: 1134-1141 - 2013
- [c1]Jose M. Alvarez, Mathieu Salzmann, Nick Barnes:
Learning appearance models for road detection. Intelligent Vehicles Symposium 2013: 423-429
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