Real image

Results: 287



#Item
11Real-Time Single Image and Video Super-Resolution Using an Efficient  arXiv:1609.05158v2 [cs.CV] 23 Sep 2016 Sub-Pixel Convolutional Neural Network Wenzhe Shi1 , Jose Caballero1 , Ferenc Husz´ar1 , Johannes Totz1 , Andr

Real-Time Single Image and Video Super-Resolution Using an Efficient arXiv:1609.05158v2 [cs.CV] 23 Sep 2016 Sub-Pixel Convolutional Neural Network Wenzhe Shi1 , Jose Caballero1 , Ferenc Husz´ar1 , Johannes Totz1 , Andr

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Source URL: arxiv.org

- Date: 2016-09-25 20:34:58
    12IMAGE PROCESSING CONSIDERATIONS FOR SIMPLE REAL-TIME RESTRICTOMETRIC FLUID-BASED USER INTERFACES Steve Mann, http://eyetap.org University of Toronto, Department of Electrical and Computer Engineering ABSTRACT The FUNtain

    IMAGE PROCESSING CONSIDERATIONS FOR SIMPLE REAL-TIME RESTRICTOMETRIC FLUID-BASED USER INTERFACES Steve Mann, http://eyetap.org University of Toronto, Department of Electrical and Computer Engineering ABSTRACT The FUNtain

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    Source URL: www.eyetap.org

    - Date: 2006-03-24 01:30:06
      13   Is   the   deconvolution   layer   the   same   as   a  convolutional   layer?   A   note   on   Real­Time   Single   Image   and   Video   Super­Resolution   

        Is   the   deconvolution   layer   the   same   as   a  convolutional   layer?   A   note   on   Real­Time   Single   Image   and   Video   Super­Resolution   

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      Source URL: arxiv.org

      - Date: 2016-09-22 20:05:44
        14Feature Article  Image-Based Interactive Exploration of Real-World

        Feature Article Image-Based Interactive Exploration of Real-World

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        Source URL: research.microsoft.com

        - Date: 2004-05-14 16:23:19
          15INTRODUCING THE ALL NEW IMAGE  REAL SOUND FOR REAL PEOPLE Image Specifications Image T6

          INTRODUCING THE ALL NEW IMAGE REAL SOUND FOR REAL PEOPLE Image Specifications Image T6

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          Source URL: www.psbspeakers.com

          - Date: 2011-05-18 18:19:47
            16To appearofinReal-Time Journal of Image Real-Time Image Processing Journal Processing

            To appearofinReal-Time Journal of Image Real-Time Image Processing Journal Processing

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            Source URL: www.ais.uni-bonn.de

            Language: English - Date: 2016-01-17 03:15:52
            17Incorporating On-demand Stereo for Real Time Recognition T. Deselaers1,2 , A. Criminisi1 , J. Winn1 and A. Agarwal1 1 Microsoft Research Ltd., Cambridge, United Kingdom 2 Human Language Technology and Pattern Recognition

            Incorporating On-demand Stereo for Real Time Recognition T. Deselaers1,2 , A. Criminisi1 , J. Winn1 and A. Agarwal1 1 Microsoft Research Ltd., Cambridge, United Kingdom 2 Human Language Technology and Pattern Recognition

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            Source URL: thomas.deselaers.de

            Language: English - Date: 2014-10-11 09:29:30
            18Single Image Deblurring for a Real-Time Face Recognition System Brian Heflin∗† , Brian Parks† , Walter Scheirer∗† , and Terrance Boult∗† ∗ Securics  Inc.

            Single Image Deblurring for a Real-Time Face Recognition System Brian Heflin∗† , Brian Parks† , Walter Scheirer∗† , and Terrance Boult∗† ∗ Securics Inc.

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            Source URL: www.vast.uccs.edu

            Language: English - Date: 2011-06-10 09:07:35
            19REAL-TIME PHOTOGRAMMETRIC INPUT VERSUS DIGITISED MAPS: ACCURACY, TIMELINESS AND COST lan Dowman and Jan-Peter Muller University College London Department of Photogrammetry and Surveying Gower Street

            REAL-TIME PHOTOGRAMMETRIC INPUT VERSUS DIGITISED MAPS: ACCURACY, TIMELINESS AND COST lan Dowman and Jan-Peter Muller University College London Department of Photogrammetry and Surveying Gower Street

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            Source URL: mapcontext.com

            Language: English - Date: 2008-08-30 01:14:53
            20A Probabilistic Framework for Real-time 3D Segmentation using Spatial, Temporal, and Semantic Cues David Held, Devin Guillory, Brice Rebsamen, Sebastian Thrun, Silvio Savarese Computer Science Department, Stanford Univer

            A Probabilistic Framework for Real-time 3D Segmentation using Spatial, Temporal, and Semantic Cues David Held, Devin Guillory, Brice Rebsamen, Sebastian Thrun, Silvio Savarese Computer Science Department, Stanford Univer

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            Source URL: davheld.github.io

            Language: English - Date: 2016-08-23 02:12:42