Panoramic Image Generation: From 2-D Sketch to Spherical Image
暂无分享,去创建一个
Chaoyi Han | Yiping Duan | Yunfei Du | Xiaoming Tao | Bingrui Geng | Jianhua Lu | Xiaoming Tao | Jianhua Lu | Yiping Duan | Bingrui Geng | Yunfei Du | Chaoyi Han
[1] Zhang Lin. Image recovery based on compressive sensing and Curvelet transform via ROMP , 2012, 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery.
[2] Yoshua Bengio,et al. Generative Adversarial Networks , 2014, ArXiv.
[3] Xiaoming Tao,et al. Saliency Prediction on Omnidirectional Image With Generative Adversarial Imitation Learning , 2019, IEEE Transactions on Image Processing.
[4] Yann LeCun,et al. Energy-based Generative Adversarial Network , 2016, ICLR.
[5] Ali Cafer Gürbüz,et al. SAR image reconstruction by expectation maximization based matching pursuit , 2015, Digit. Signal Process..
[6] Alex Graves,et al. Conditional Image Generation with PixelCNN Decoders , 2016, NIPS.
[7] S.M. Elshoura,et al. Analysis of noise sensitivity and reconstruction accuracy of Tchebichef moments , 2008, IEEE SoutheastCon 2008.
[8] M. Yuan,et al. Model selection and estimation in regression with grouped variables , 2006 .
[9] Zulin Wang,et al. Predicting Head Movement in Panoramic Video: A Deep Reinforcement Learning Approach , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[10] Joel A. Tropp,et al. Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit , 2007, IEEE Transactions on Information Theory.
[11] Mike E. Davies,et al. Iterative Hard Thresholding for Compressed Sensing , 2008, ArXiv.
[12] Antonio M. López,et al. The SYNTHIA Dataset: A Large Collection of Synthetic Images for Semantic Segmentation of Urban Scenes , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[13] Bernt Schiele,et al. Learning What and Where to Draw , 2016, NIPS.
[14] Karen O. Egiazarian,et al. Compressed Sensing Image Reconstruction Via Recursive Spatially Adaptive Filtering , 2007, ICIP.
[15] Stéphane Mallat,et al. Solving Inverse Problems With Piecewise Linear Estimators: From Gaussian Mixture Models to Structured Sparsity , 2010, IEEE Transactions on Image Processing.
[16] Yunsong Li,et al. Hyperspectral image reconstruction by deep convolutional neural network for classification , 2017, Pattern Recognit..
[17] Sepp Hochreiter,et al. GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium , 2017, NIPS.
[18] Lei Zhang,et al. Nonlocally Centralized Sparse Representation for Image Restoration , 2013, IEEE Transactions on Image Processing.
[19] Gregory K. Wallace,et al. The JPEG still picture compression standard , 1991, CACM.
[20] Joel A. Tropp,et al. Greed is good: algorithmic results for sparse approximation , 2004, IEEE Transactions on Information Theory.
[21] Sebastian Ramos,et al. The Cityscapes Dataset for Semantic Urban Scene Understanding , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[22] Léon Bottou,et al. Wasserstein Generative Adversarial Networks , 2017, ICML.
[23] R. DeVore,et al. Compressed sensing and best k-term approximation , 2008 .
[24] Zulin Wang,et al. Assessing Visual Quality of Omnidirectional Videos , 2019, IEEE Transactions on Circuits and Systems for Video Technology.
[25] Max Welling,et al. Spherical CNNs , 2018, ICLR.
[26] Michel Barlaud,et al. Image coding using wavelet transform , 1992, IEEE Trans. Image Process..
[27] Naokazu Yokoya,et al. Generation of high-resolution stereo panoramic images by omnidirectional imaging sensor using hexagonal pyramidal mirrors , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).
[28] 拓海 杉山,et al. “Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告 , 2017 .
[30] Wojciech Zaremba,et al. Improved Techniques for Training GANs , 2016, NIPS.
[31] Yücel Altunbasak,et al. Super-resolution reconstruction of compressed video using transform-domain statistics , 2004, IEEE Transactions on Image Processing.
[32] Lei Zhang,et al. Image Deblurring and Super-Resolution by Adaptive Sparse Domain Selection and Adaptive Regularization , 2010, IEEE Transactions on Image Processing.
[33] S. Frick,et al. Compressed Sensing , 2014, Computer Vision, A Reference Guide.
[34] Yee Whye Teh,et al. A Fast Learning Algorithm for Deep Belief Nets , 2006, Neural Computation.
[35] Guanghui Wang,et al. Adversarially Approximated Autoencoder for Image Generation and Manipulation , 2019, IEEE Transactions on Multimedia.
[36] Thong T. Do,et al. Sparsity adaptive matching pursuit algorithm for practical compressed sensing , 2008, 2008 42nd Asilomar Conference on Signals, Systems and Computers.
[37] Nir Shavit,et al. Generative Compression , 2017, 2018 Picture Coding Symposium (PCS).
[38] Thomas Brox,et al. Generating Images with Perceptual Similarity Metrics based on Deep Networks , 2016, NIPS.
[39] Wotao Yin,et al. Bregman Iterative Algorithms for (cid:2) 1 -Minimization with Applications to Compressed Sensing ∗ , 2008 .
[40] Lei Zhang,et al. Centralized sparse representation for image restoration , 2011, 2011 International Conference on Computer Vision.
[41] Fang Liu,et al. Local Maximal Homogeneous Region Search for SAR Speckle Reduction With Sketch-Based Geometrical Kernel Function , 2014, IEEE Transactions on Geoscience and Remote Sensing.
[42] Bin Dong,et al. Fast Linearized Bregman Iteration for Compressive Sensing and Sparse Denoising , 2011, ArXiv.
[43] Meenakshi,et al. Image reconstruction using modified orthogonal matching pursuit and compressive sensing , 2015, International Conference on Computing, Communication & Automation.
[44] T. Charles Clancy,et al. Over-the-Air Deep Learning Based Radio Signal Classification , 2017, IEEE Journal of Selected Topics in Signal Processing.
[45] Mark A. Anastasio,et al. Deep Learning-Guided Image Reconstruction from Incomplete Data , 2017, ArXiv.
[46] Alexei A. Efros,et al. Image-to-Image Translation with Conditional Adversarial Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[47] David Zhang,et al. A Survey of Sparse Representation: Algorithms and Applications , 2015, IEEE Access.
[48] Max Welling,et al. Group Equivariant Convolutional Networks , 2016, ICML.
[49] Stéphane Mallat,et al. Matching pursuits with time-frequency dictionaries , 1993, IEEE Trans. Signal Process..
[50] Mário A. T. Figueiredo,et al. Gradient Projection for Sparse Reconstruction: Application to Compressed Sensing and Other Inverse Problems , 2007, IEEE Journal of Selected Topics in Signal Processing.
[51] H. Barlow. Vision: A computational investigation into the human representation and processing of visual information: David Marr. San Francisco: W. H. Freeman, 1982. pp. xvi + 397 , 1983 .
[52] Song-Chun Zhu,et al. Primal sketch: Integrating structure and texture , 2007, Comput. Vis. Image Underst..
[53] Luc Van Gool,et al. Generative Adversarial Networks for Extreme Learned Image Compression , 2018, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[54] Yang Yang,et al. 2D-to-Stereo Panorama Conversion Using GAN and Concentric Mosaics , 2019, IEEE Access.
[55] Chinmoy Bhattacharya,et al. A Discrete Wavelet Transform Approach to Multiresolution Complex SAR Image Generation , 2007, IEEE Geoscience and Remote Sensing Letters.
[56] 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.
[57] Jean-Luc Starck,et al. Image reconstruction by the wavelet transform applied to aperture synthesis , 1994 .
[58] Hairong Yang,et al. A new compressed sensing-based matching pursuit algorithm for image reconstruction , 2012, 2012 5th International Congress on Image and Signal Processing.
[59] Sim Heng Ong,et al. Image Analysis by Tchebichef Moments , 2001, IEEE Trans. Image Process..
[60] Pavan Turaga,et al. Convolutional Neural Networks for Noniterative Reconstruction of Compressively Sensed Images , 2017, IEEE Transactions on Computational Imaging.
[61] Yibo Zhang,et al. Phase recovery and holographic image reconstruction using deep learning in neural networks , 2017, Light: Science & Applications.
[62] Christian Ledig,et al. Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[63] Chuang Gan,et al. Sparse, Smart Contours to Represent and Edit Images , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.