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Personalized Federated Learning with First Order Model Optimization


Jan 28, 2021
Michael Zhang, Karan Sapra, Sanja Fidler, Serena Yeung, Jose M. Alvarez

* ICLR 2021 

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Scalable Active Learning for Object Detection


Apr 09, 2020
Elmar Haussmann, Michele Fenzi, Kashyap Chitta, Jan Ivanecky, Hanson Xu, Donna Roy, Akshita Mittel, Nicolas Koumchatzky, Clement Farabet, Jose M. Alvarez

* accepted at IEEE-IV2020 

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Context Based Emotion Recognition using EMOTIC Dataset


Mar 30, 2020
Ronak Kosti, Jose M. Alvarez, Adria Recasens, Agata Lapedriza


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Dreaming to Distill: Data-free Knowledge Transfer via DeepInversion


Dec 18, 2019
Hongxu Yin, Pavlo Molchanov, Zhizhong Li, Jose M. Alvarez, Arun Mallya, Derek Hoiem, Niraj K. Jha, Jan Kautz


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Cost Volume Pyramid Based Depth Inference for Multi-View Stereo


Dec 18, 2019
Jiayu Yang, Wei Mao, Jose M. Alvarez, Miaomiao Liu


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VACL: Variance-Aware Cross-Layer Regularization for Pruning Deep Residual Networks


Sep 10, 2019
Shuang Gao, Xin Liu, Lung-Sheng Chien, William Zhang, Jose M. Alvarez

* ICCV Workshop 

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Quadtree Generating Networks: Efficient Hierarchical Scene Parsing with Sparse Convolutions


Jul 27, 2019
Kashyap Chitta, Jose M. Alvarez, Martial Hebert


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Less is More: An Exploration of Data Redundancy with Active Dataset Subsampling


May 29, 2019
Kashyap Chitta, Jose M. Alvarez, Elmar Haussmann, Clement Farabet


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ExpandNets: Exploiting Linear Redundancy to Train Small Networks


Dec 12, 2018
Shuxuan Guo, Jose M. Alvarez, Mathieu Salzmann


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Large-Scale Visual Active Learning with Deep Probabilistic Ensembles


Nov 30, 2018
Kashyap Chitta, Jose M. Alvarez, Adam Lesnikowski

* arXiv admin note: text overlap with arXiv:1811.02640 

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Deep Probabilistic Ensembles: Approximate Variational Inference through KL Regularization


Nov 30, 2018
Kashyap Chitta, Jose M. Alvarez, Adam Lesnikowski

* Workshop on Bayesian Deep Learning (NeurIPS 2018) 

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The Relevance of Bayesian Layer Positioning to Model Uncertainty in Deep Bayesian Active Learning


Nov 29, 2018
Jiaming Zeng, Adam Lesnikowski, Jose M. Alvarez

* Third workshop on Bayesian Deep Learning (NeurIPS 2018) 

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Effective Use of Synthetic Data for Urban Scene Semantic Segmentation


Jul 16, 2018
Fatemeh Sadat Saleh, Mohammad Sadegh Aliakbarian, Mathieu Salzmann, Lars Petersson, Jose M. Alvarez

* Accepted in European Conference on Computer Vision (ECCV), 2018 

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Compression-aware Training of Deep Networks


Nov 13, 2017
Jose M. Alvarez, Mathieu Salzmann

* Accepted at NIPS 2017 

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Bringing Background into the Foreground: Making All Classes Equal in Weakly-supervised Video Semantic Segmentation


Aug 15, 2017
Fatemeh Sadat Saleh, Mohammad Sadegh Aliakbarian, Mathieu Salzmann, Lars Petersson, Jose M. Alvarez

* 11 pages, 4 figures, 7 tables, Accepted in ICCV 2017 

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Class-Weighted Convolutional Features for Visual Instance Search


Jul 09, 2017
Albert Jimenez, Jose M. Alvarez, Xavier Giro-i-Nieto

* To appear in the British Machine Vision Conference (BMVC), September 2017 

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Incorporating Network Built-in Priors in Weakly-supervised Semantic Segmentation


Jun 06, 2017
Fatemeh Sadat Saleh, Mohammad Sadegh Aliakbarian, Mathieu Salzmann, Lars Petersson, Jose M. Alvarez, Stephen Gould

* 14 pages, 11 figures, 8 tables, Accepted in IEEE Transaction on Pattern Analysis and Machine Intelligence (IEEE TPAMI) 

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Built-in Foreground/Background Prior for Weakly-Supervised Semantic Segmentation


Sep 02, 2016
Fatemehsadat Saleh, Mohammad Sadegh Ali Akbarian, Mathieu Salzmann, Lars Petersson, Stephen Gould, Jose M. Alvarez

* Accepted in ECCV 2016 

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Learning Image Matching by Simply Watching Video


Mar 29, 2016
Gucan Long, Laurent Kneip, Jose M. Alvarez, Hongdong Li

* The second version contains additional quantitative evaluation of frame interpolation 

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Road Detection by One-Class Color Classification: Dataset and Experiments


Dec 18, 2014
Jose M. Alvarez, Theo Gevers, Antonio M. Lopez

* 10 pages 

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