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You Only Group Once: Efficient Point-Cloud Processing with Token Representation and Relation Inference Module


Mar 24, 2021
Chenfeng Xu, Bohan Zhai, Bichen Wu, Tian Li, Wei Zhan, Peter Vajda, Kurt Keutzer, Masayoshi Tomizuka

* The code is available at https://github.com/chenfengxu714/YOGO.git 

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Unbiased Teacher for Semi-Supervised Object Detection


Feb 18, 2021
Yen-Cheng Liu, Chih-Yao Ma, Zijian He, Chia-Wen Kuo, Kan Chen, Peizhao Zhang, Bichen Wu, Zsolt Kira, Peter Vajda

* Accepted to ICLR 2021; Code is available at https://github.com/facebookresearch/unbiased-teacher 

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FBWave: Efficient and Scalable Neural Vocoders for Streaming Text-To-Speech on the Edge


Nov 25, 2020
Bichen Wu, Qing He, Peizhao Zhang, Thilo Koehler, Kurt Keutzer, Peter Vajda


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One Shot 3D Photography


Sep 01, 2020
Johannes Kopf, Kevin Matzen, Suhib Alsisan, Ocean Quigley, Francis Ge, Yangming Chong, Josh Patterson, Jan-Michael Frahm, Shu Wu, Matthew Yu, Peizhao Zhang, Zijian He, Peter Vajda, Ayush Saraf, Michael Cohen

* ACM Transactions on Graphics (Proceedings of SIGGRAPH 2020), Volume 39, Number 4, 2020 
* Project page: https://facebookresearch.github.io/one_shot_3d_photography/ Code: https://github.com/facebookresearch/one_shot_3d_photography 

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Geometric Correspondence Fields: Learned Differentiable Rendering for 3D Pose Refinement in the Wild


Jul 17, 2020
Alexander Grabner, Yaming Wang, Peizhao Zhang, Peihong Guo, Tong Xiao, Peter Vajda, Peter M. Roth, Vincent Lepetit

* Accepted to European Conference on Computer Vision (ECCV) 2020 

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Visual Transformers: Token-based Image Representation and Processing for Computer Vision


Jul 02, 2020
Bichen Wu, Chenfeng Xu, Xiaoliang Dai, Alvin Wan, Peizhao Zhang, Masayoshi Tomizuka, Kurt Keutzer, Peter Vajda


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FBNetV3: Joint Architecture-Recipe Search using Neural Acquisition Function


Jun 07, 2020
Xiaoliang Dai, Alvin Wan, Peizhao Zhang, Bichen Wu, Zijian He, Zhen Wei, Kan Chen, Yuandong Tian, Matthew Yu, Peter Vajda, Joseph E. Gonzalez


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FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions


Apr 12, 2020
Alvin Wan, Xiaoliang Dai, Peizhao Zhang, Zijian He, Yuandong Tian, Saining Xie, Bichen Wu, Matthew Yu, Tao Xu, Kan Chen, Peter Vajda, Joseph E. Gonzalez

* 8 pages, 10 figures, accepted to CVPR 2020 

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Deep Space-Time Video Upsampling Networks


Apr 06, 2020
Jaeyeon Kang, Younghyun Jo, Seoung Wug Oh, Peter Vajda, Seon Joo Kim


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SqueezeSegV3: Spatially-Adaptive Convolution for Efficient Point-Cloud Segmentation


Apr 03, 2020
Chenfeng Xu, Bichen Wu, Zining Wang, Wei Zhan, Peter Vajda, Kurt Keutzer, Masayoshi Tomizuka

* Code and data are available at: https://github.com/chenfengxu714/SqueezeSegV3.git 

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Learning the Loss Functions in a Discriminative Space for Video Restoration


Mar 20, 2020
Younghyun Jo, Jaeyeon Kang, Seoung Wug Oh, Seonghyeon Nam, Peter Vajda, Seon Joo Kim

* 24 pages 

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Efficient Segmentation: Learning Downsampling Near Semantic Boundaries


Jul 16, 2019
Dmitrii Marin, Zijian He, Peter Vajda, Priyam Chatterjee, Sam Tsai, Fei Yang, Yuri Boykov


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Learning to Generate Grounded Image Captions without Localization Supervision


Jun 01, 2019
Chih-Yao Ma, Yannis Kalantidis, Ghassan AlRegib, Peter Vajda, Marcus Rohrbach, Zsolt Kira


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Precision Highway for Ultra Low-Precision Quantization


Dec 24, 2018
Eunhyeok Park, Dongyoung Kim, Sungjoo Yoo, Peter Vajda


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ChamNet: Towards Efficient Network Design through Platform-Aware Model Adaptation


Dec 21, 2018
Xiaoliang Dai, Peizhao Zhang, Bichen Wu, Hongxu Yin, Fei Sun, Yanghan Wang, Marat Dukhan, Yunqing Hu, Yiming Wu, Yangqing Jia, Peter Vajda, Matt Uyttendaele, Niraj K. Jha


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FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search


Dec 14, 2018
Bichen Wu, Xiaoliang Dai, Peizhao Zhang, Yanghan Wang, Fei Sun, Yiming Wu, Yuandong Tian, Peter Vajda, Yangqing Jia, Kurt Keutzer


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Mixed Precision Quantization of ConvNets via Differentiable Neural Architecture Search


Nov 30, 2018
Bichen Wu, Yanghan Wang, Peizhao Zhang, Yuandong Tian, Peter Vajda, Kurt Keutzer


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Value-aware Quantization for Training and Inference of Neural Networks


Apr 20, 2018
Eunhyeok Park, Sungjoo Yoo, Peter Vajda


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DSD: Dense-Sparse-Dense Training for Deep Neural Networks


Feb 21, 2017
Song Han, Jeff Pool, Sharan Narang, Huizi Mao, Enhao Gong, Shijian Tang, Erich Elsen, Peter Vajda, Manohar Paluri, John Tran, Bryan Catanzaro, William J. Dally

* Published as a conference paper at ICLR 2017 

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