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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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