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Boosting Supervised Learning Performance with Co-training


Nov 18, 2021
Xinnan Du, William Zhang, Jose M. Alvarez

* 2021 IEEE Intelligent Vehicles Symposium 

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When to Prune? A Policy towards Early Structural Pruning


Oct 22, 2021
Maying Shen, Pavlo Molchanov, Hongxu Yin, Jose M. Alvarez


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HALP: Hardware-Aware Latency Pruning


Oct 20, 2021
Maying Shen, Hongxu Yin, Pavlo Molchanov, Lei Mao, Jianna Liu, Jose M. Alvarez


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Panoptic SegFormer


Sep 11, 2021
Zhiqi Li, Wenhai Wang, Enze Xie, Zhiding Yu, Anima Anandkumar, Jose M. Alvarez, Tong Lu, Ping Luo

* Technical Report 

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Deep Neural Networks are Surprisingly Reversible: A Baseline for Zero-Shot Inversion


Jul 13, 2021
Xin Dong, Hongxu Yin, Jose M. Alvarez, Jan Kautz, Pavlo Molchanov

* A new inversion method to reverse neural networks and get input from intermediate feature maps. Works without original data for classifiers and GANs 

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Towards Reducing Labeling Cost in Deep Object Detection


Jun 22, 2021
Ismail Elezi, Zhiding Yu, Anima Anandkumar, Laura Leal-Taixe, Jose M. Alvarez

* Includes supplementary material 

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Distilling Image Classifiers in Object Detectors


Jun 09, 2021
Shuxuan Guo, Jose M. Alvarez, Mathieu Salzmann


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SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers


Jun 05, 2021
Enze Xie, Wenhai Wang, Zhiding Yu, Anima Anandkumar, Jose M. Alvarez, Ping Luo

* Tech Report 

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See through Gradients: Image Batch Recovery via GradInversion


Apr 15, 2021
Hongxu Yin, Arun Mallya, Arash Vahdat, Jose M. Alvarez, Jan Kautz, Pavlo Molchanov

* CVPR 2021 accepted paper 

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Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection


Apr 12, 2021
Nadine Chang, Zhiding Yu, Yu-Xiong Wang, Anima Anandkumar, Sanja Fidler, Jose M. Alvarez


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Self-supervised Learning of Depth Inference for Multi-view Stereo


Apr 07, 2021
Jiayu Yang, Jose M. Alvarez, Miaomiao Liu

* CVPR 2021 

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Contrastive Syn-to-Real Generalization


Apr 06, 2021
Wuyang Chen, Zhiding Yu, Shalini De Mello, Sifei Liu, Jose M. Alvarez, Zhangyang Wang, Anima Anandkumar

* Accepted in ICLR 2021 

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Active Learning for Deep Object Detection via Probabilistic Modeling


Mar 30, 2021
Jiwoong Choi, Ismail Elezi, Hyuk-Jae Lee, Clement Farabet, Jose M. Alvarez


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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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