A Deep Learning Based Method to Discriminate Between Photorealistic Computer Generated Images and Photographic Images
暂无分享,去创建一个
[1] Vipin Tyagi,et al. Methods to Distinguish Photorealistic Computer Generated Images from Photographic Images: A Review , 2019, ICACDS.
[2] Kilian Q. Weinberger,et al. Densely Connected Convolutional Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[3] Xiangyang Luo,et al. Identifying Computer Generated Images Based on Quaternion Central Moments in Color Quaternion Wavelet Domain , 2019, IEEE Transactions on Circuits and Systems for Video Technology.
[4] Vipin Tyagi,et al. A hybrid copy-move image forgery detection technique based on Fourier-Mellin and scale invariant feature transforms , 2020, Multimedia Tools and Applications.
[5] Robert M. Haralick,et al. Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..
[6] Qi Cui. Identifying materials of photographic images and photorealistic computer generated graphics based on deep CNNs , 2018 .
[7] Wang-Q Lim,et al. Compactly supported shearlets are optimally sparse , 2010, J. Approx. Theory.
[8] Ming He,et al. Distinguish computer generated and digital images: A CNN solution , 2018, Concurr. Comput. Pract. Exp..
[9] Wang Rangding,et al. Classifying computer generated graphics and natural image based on image contour information , 2012 .
[10] Li Fei-Fei,et al. ImageNet: A large-scale hierarchical image database , 2009, CVPR.
[11] Alin C. Popescu,et al. Exposing digital forgeries in color filter array interpolated images , 2005, IEEE Transactions on Signal Processing.
[12] Dong-Ming Yan,et al. Distinguishing Between Natural and Computer-Generated Images Using Convolutional Neural Networks , 2018, IEEE Transactions on Information Forensics and Security.
[13] Vipin Tyagi,et al. Image Forgery Detection: Survey and Future Directions , 2019, Data, Engineering and Applications.
[14] S. P. Ghrera,et al. Pixel-Based Image Forgery Detection: A Review , 2014 .
[15] Xinghao Jiang,et al. Computer Graphics Identification Combining Convolutional and Recurrent Neural Networks , 2018, IEEE Signal Processing Letters.
[16] Bill Triggs,et al. Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[17] Shih-Fu Chang,et al. Columbia Photographic Images and Photorealistic Computer Graphics Dataset , 2005 .
[18] Guohua Wu,et al. An Evaluation of Deep Learning-Based Computer Generated Image Detection Approaches , 2019, IEEE Access.
[19] Shih-Fu Chang,et al. Identifying and prefiltering images , 2009, IEEE Signal Process. Mag..
[20] Philip Howard,et al. A Study of Misinformation in WhatsApp groups with a focus on the Brazilian Presidential Elections. , 2019, WWW.
[21] Larry S. Davis,et al. A novel feature descriptor based on the shearlet transform , 2011, 2011 18th IEEE International Conference on Image Processing.
[22] 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.
[23] Anderson Rocha,et al. Computer generated images vs. digital photographs: A synergetic feature and classifier combination approach , 2013, J. Vis. Commun. Image Represent..
[24] Ruoyu Wu,et al. Identifying computer generated graphics VIA histogram features , 2011, 2011 18th IEEE International Conference on Image Processing.
[25] Tao Zhang,et al. Identifying photorealistic computer graphics using second-order difference statistics , 2010, 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery.
[26] E. Candès,et al. Curvelets: A Surprisingly Effective Nonadaptive Representation for Objects with Edges , 2000 .
[27] Matti Pietikäinen,et al. A Generalized Local Binary Pattern Operator for Multiresolution Gray Scale and Rotation Invariant Texture Classification , 2001, ICAPR.
[28] Siwei Lyu,et al. How realistic is photorealistic , 2005 .
[29] Vipin Tyagi,et al. A copy-move image forgery detection technique based on tetrolet transform , 2020, J. Inf. Secur. Appl..
[30] L. Liebovitch,et al. A fast algorithm to determine fractal dimensions by box counting , 1989 .
[31] Kunj Bihari Meena,et al. A Novel Method to Distinguish Photorealistic Computer Generated Images from Photographic Images , 2019, 2019 Fifth International Conference on Image Information Processing (ICIIP).
[32] Tiago Carvalho,et al. Detecting Computer Generated Images with Deep Convolutional Neural Networks , 2017, 2017 30th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI).
[33] Vipin Tyagi,et al. Understanding Digital Image Processing , 2018 .
[34] Vipin Tyagi,et al. A copy-move image forgery detection technique based on Gaussian-Hermite moments , 2019, Multimedia Tools and Applications.