Computer Graphics Identification Combining Convolutional and Recurrent Neural Networks
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Xinghao Jiang | Tanfeng Sun | Haoliang Li | Peisong He | Tanfeng Sun | Xinghao Jiang | Haoliang Li | Peisong He
[1] Siwei Lyu,et al. Higher-order Wavelet Statistics and their Application to Digital Forensics , 2003, 2003 Conference on Computer Vision and Pattern Recognition Workshop.
[2] Yun Q. Shi,et al. Identifying Computer Graphics using HSV Color Model and Statistical Moments of Characteristic Functions , 2007, 2007 IEEE International Conference on Multimedia and Expo.
[3] Feng Pan,et al. Discriminating between photorealistic computer graphics and natural images using fractal geometry , 2009, Science in China Series F: Information Sciences.
[4] Jianhua Li,et al. Identifying computer generated and digital camera images using fractional lower order moments , 2009, 2009 4th IEEE Conference on Industrial Electronics and Applications.
[5] Weidong Min,et al. DETECTING THE COMPOSITE OF PHOTOGRAPHIC IMAGE AND COMPUTER GENERATED IMAGE COMBINING WITH COLOR , TEXTURE AND SHAPE FEATURE , 2013 .
[6] Anderson Rocha,et al. Computer generated images vs. digital photographs: A synergetic feature and classifier combination approach , 2013, J. Vis. Commun. Image Represent..
[7] Paul J. Werbos,et al. Backpropagation Through Time: What It Does and How to Do It , 1990, Proc. IEEE.
[8] Siwei Lyu,et al. How realistic is photorealistic? , 2005, IEEE Transactions on Signal Processing.
[9] Jan Kautz,et al. High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[10] Jian Sun,et al. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[11] Belhassen Bayar,et al. On the robustness of constrained convolutional neural networks to JPEG post-compression for image resampling detection , 2017, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[12] Yun Q. Shi,et al. Distinguishing Computer Graphics from Photographic Images Using Local Binary Patterns , 2012, IWDW.
[13] Jianru Xue,et al. A statistical feature based approach to distinguish PRCG from photographs , 2014, Comput. Vis. Image Underst..
[14] Paolo Bestagini,et al. First Steps Toward Camera Model Identification With Convolutional Neural Networks , 2016, IEEE Signal Processing Letters.
[15] Ismail Avcibas,et al. Differentiating Between Images Using Wavelet-Based Transforms: A Comparative Study , 2011, IEEE Transactions on Information Forensics and Security.
[16] Gang Wang,et al. DAG-Recurrent Neural Networks for Scene Labeling , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[17] Geoffrey E. Hinton,et al. Rectified Linear Units Improve Restricted Boltzmann Machines , 2010, ICML.
[18] H. P. Chen,et al. Detecting computer generated images based on local ternary count , 2016, Pattern Recognition and Image Analysis.
[19] Shiguo Lian,et al. Forensics feature analysis in quaternion wavelet domain for distinguishing photographic images and computer graphics , 2017, Multimedia Tools and Applications.
[20] Fei Peng,et al. Identification of Natural Images and Computer‐Generated Graphics Based on Statistical and Textural Features , 2015, Journal of forensic sciences.
[21] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[22] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[23] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.
[24] Fei Peng,et al. Discrimination of natural images and computer generated graphics based on multi-fractal and regression analysis , 2017 .
[25] Dong-Ming Yan,et al. Distinguishing Between Natural and Computer-Generated Images Using Convolutional Neural Networks , 2018, IEEE Transactions on Information Forensics and Security.
[26] Ming Yang,et al. 3D Convolutional Neural Networks for Human Action Recognition , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[27] Jong-Uk Hou,et al. Identifying photorealistic computer graphics using convolutional neural networks , 2017, 2017 IEEE International Conference on Image Processing (ICIP).
[28] Min Wu,et al. Information Forensics: An Overview of the First Decade , 2013, IEEE Access.
[29] James Martens,et al. Deep learning via Hessian-free optimization , 2010, ICML.
[30] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[31] Stacy Holman Jones. Torch , 1999 .
[32] Junichi Yamagishi,et al. Distinguishing computer graphics from natural images using convolution neural networks , 2017, 2017 IEEE Workshop on Information Forensics and Security (WIFS).
[33] Paolo Bestagini,et al. Aligned and Non-Aligned Double JPEG Detection Using Convolutional Neural Networks , 2017, J. Vis. Commun. Image Represent..
[34] Shih-Fu Chang,et al. Physics-motivated features for distinguishing photographic images and computer graphics , 2005, ACM Multimedia.
[35] Z. Jane Wang,et al. Median Filtering Forensics Based on Convolutional Neural Networks , 2015, IEEE Signal Processing Letters.
[36] Jiangqun Ni,et al. A deep learning approach to detection of splicing and copy-move forgeries in images , 2016, 2016 IEEE International Workshop on Information Forensics and Security (WIFS).
[37] Alex ChiChung Kot,et al. Image Recapture Detection with Convolutional and Recurrent Neural Networks , 2017, Media Watermarking, Security, and Forensics.
[38] Cordelia Schmid,et al. Constructing models for content-based image retrieval , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.