1st and 2nd FM generation 3D halftoning133-MEGAPIXEL1 MICRON PIXELS180 degree images1-bit matrix completion100 Hue test108 Megapixel1/f noise
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2D VIEWS2D DCT2.5D reconstruction2D-plus-depth video2D and 3D video2D metrics2-d scale2D to Hologram conversion2D AND 3D CONVERTIBLE DISPLAY2.5D printing2D/3D imaging, high performance computing, imaging systems, efficient computations and storage2.5D PRINTING2.5 D printing2D printing2-D barcodes2D-TO-3D CONVERSION ARTIFACTS2AFC2D2.5D
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3D depth sensing3D range scanning3D Curvelet3ARRI footage360° video360 IMAGING3D HALFTONING3D digital halftoning3D Vision3D Immersion3D rigid transformations3D RECONSTRUCTION3D modeling3D/2D Visuals3D Point Cloud3D affine transformation3D recovery3D Printing3D scanning3D Mapping3D capture3D modelling360 degree images3D Range Data Compression3D shape3D PRINTER3D Communications360-degree content3D printing3D-HEVC3D adaptive halftoning3D Halftoning3D Data Sources3D camera3D Digital Image Correlation3D image compression3D Tracking3D EDUCATIONAL MATERIAL3D Video Communications3D Shape Indexing and Retrieval3D/4D DATA PROCESSING AND FILTERING360-degree videos3D connected tube model3D scene flow estimation3D Modeling3D STACK3D surface reproduction3D Range Data360-degree Image3D model3D compression3D Imaging3D TRANSFORMATION3D warping3D objects3D scene classification3D video processing3D data processing3D optical scans3D Saliency3D surface360-degree video streaming3D depth-map360-video3D/4D Data Processing and Filtering360VR3D mapping and localization3D stereo vision360 panorama3D perception3D CAMERAS360 degrees video360-degree art exhibition360-degree image projection3D video3D-LUT3D/4D Scanning3D face alignment3D PRINTING3D MODEL3D Object Detection360-degree images3D Morphable Model3D Data Processing3D Telepresence3D DIGITIZATION METHOD FOR OIL PAINTINGS3D position measurement of people3D-shooting3D Measurement3D theater program listing3D refinement3D-color perception3D display3D mesh3D shape indexing and retrieval3D object shape3D Computer Graphics3D Compression3D Models3d localization3D MODELLING3-D RECONSTRUCTION3D RANGE IMAGING3D Image Processing3D Quality3D Video Conferencing3D shape analysis360-DEGREE IMAGE360-deg quality assessment3D SHAPE INDEXING AND RETRIEVAL3D SCENE RECONSTRUCTION AND MODELING3D and 2D3D print3D halftoning3D recursive search3D-human body detection3-T pixel3D Video3D SALIENCY3D Meshes3D reconstruction3D VISUALIZATION3D Compression and Encryption3DMM3D-CNN3D Lidar3D Scene Reconstruction360° STEREO PANORAMAS3D Iterative Halftoning3D MESH3D displays360-degree video3D communications3DViewers3DSR3D Gaussian splatting360-degree3D MESHES3D Display3D glasses3D COMPRESSION AND ENCRYPTION3D surface structure based halftoning3D vision3D encoding3D3D IMAGE3d video3D STIMULI3D-printing3D Range Data Encoding3d360-degree imaging3D Color Printing3D Reconstruction3D PROFILE360-Degree Video Technology3D cinema and TV3D TV3D USER INTERFACES3D DISPLAY3D-high efficiency video coding3D visual representation360 Video3A ALGORITHMS360x3D scene capture3-D SHAPE RECOVERY3d mapping3D RECOVERY3D printer360° VIDEO3D INTERACTION3D ACQUISITION ARCHITECTURE3D audio3D imaging3D range geometry3D digitization and dissemination3D localization and mapping3D colour Digital Image Correlation3D Print Appearance3D-assisted features3D localization3D/4D SCANNING3D projector3D mesh simplification35MM FILM DIGITIZATION3D human-centered technologies3D point cloud3D Scene Reconstruction and Modeling3DCNN3D-Anisotropic smoothing
Images posted online present a privacy concern in that they may be used as reference examples for a facial recognition system. Such abuse of images is in violation of privacy rights but is difficult to counter. It is well established that adversarial example images can be created for recognition systems which are based on deep neural networks. These adversarial examples can be used to disrupt the utility of the images as reference examples or training data. In this work we use a Generative Adversarial Network (GAN) to create adversarial examples to deceive facial recognition and we achieve an acceptable success rate in fooling the face recognition. Our results reduce the training time for the GAN by removing the discriminator component. Furthermore, our results show knowledge distillation can be employed to drastically reduce the size of the resulting model without impacting performance indicating that our contribution could run comfortably on a smartphone.