A Novel Framework for Image-to-image Translation and Image Compression

A Novel Framework for Image-to-image Translation and Image Compression I2I encoder I2I decoder Image encoder Image decoder UI2I encoder UI2I decoder mode=T UI2I encoder UI2I decoder mode=A (a) (b) T

[1]  拓海 杉山,et al.  “Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告 , 2017 .

[2]  장윤희,et al.  Y. , 2003, Industrial and Labor Relations Terms.

[3]  Gorjan Alagic,et al.  #p , 2019, Quantum information & computation.

[4]  P. Alam.  ‘A’ , 2021, Composites Engineering: An A–Z Guide.

[5]  Kwang In Kim,et al.  Unsupervised Attention-guided Image to Image Translation , 2018, NeurIPS.

[6]  Tsuyoshi Murata,et al.  {m , 1934, ACML.

[7]  P. Alam,et al.  R , 1823, The Herodotus Encyclopedia.

[8]  P. Alam.  ‘E’ , 2021, Composites Engineering: An A–Z Guide.

[9]  Fuxin Li,et al.  Adaptive Wing Loss for Robust Face Alignment via Heatmap Regression , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[10]  P. Alam.  ‘G’ , 2021, Composites Engineering: An A–Z Guide.

[11]  Joost van de Weijer,et al.  Image-to-image translation for cross-domain disentanglement , 2018, NeurIPS.

[12]  Luc Van Gool,et al.  Generative Adversarial Networks for Extreme Learned Image Compression , 2018, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[13]  Jung-Woo Ha,et al.  StarGAN v2: Diverse Image Synthesis for Multiple Domains , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[14]  David Minnen,et al.  Variational image compression with a scale hyperprior , 2018, ICLR.

[15]  P. Alam.  ‘L’ , 2021, Composites Engineering: An A–Z Guide.

[16]  Jane You,et al.  Efficient and Effective Context-Based Convolutional Entropy Modeling for Image Compression , 2019, IEEE Transactions on Image Processing.

[17]  Miss A.O. Penney.  (b) , 1974, The New Yale Book of Quotations.

[18]  Siwei Ma,et al.  Mode Seeking Generative Adversarial Networks for Diverse Image Synthesis , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[19]  Joost van de Weijer,et al.  Variable Rate Deep Image Compression With Modulated Autoencoder , 2019, IEEE Signal Processing Letters.

[20]  Yash Patel,et al.  Hierarchical Auto-Regressive Model for Image Compression Incorporating Object Saliency and a Deep Perceptual Loss , 2020, ArXiv.

[21]  Jan Kautz,et al.  Multimodal Unsupervised Image-to-Image Translation , 2018, ECCV.

[22]  Jungwon Lee,et al.  Variable Rate Deep Image Compression With a Conditional Autoencoder , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[23]  Xiaoming Yu,et al.  Multi-mapping Image-to-Image Translation via Learning Disentanglement , 2019, NeurIPS.

[24]  Jooyoung Lee,et al.  Context-adaptive Entropy Model for End-to-end Optimized Image Compression , 2018, ICLR.

[25]  Alexei A. Efros,et al.  Image-to-Image Translation with Conditional Adversarial Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[26]  P. Alam.  ‘K’ , 2021, Composites Engineering.

[27]  Jan Kautz,et al.  Few-shot Video-to-Video Synthesis , 2019, NeurIPS.

[28]  Philip Bachman,et al.  Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data , 2018, ICML.

[29]  Ping Tan,et al.  DualGAN: Unsupervised Dual Learning for Image-to-Image Translation , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

[30]  Alexei A. Efros,et al.  Toward Multimodal Image-to-Image Translation , 2017, NIPS.

[31]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[32]  Jan Kautz,et al.  Unsupervised Image-to-Image Translation Networks , 2017, NIPS.

[33]  Yochai Blau,et al.  Rethinking Lossy Compression: The Rate-Distortion-Perception Tradeoff , 2019, ICML.

[34]  David Minnen,et al.  Channel-Wise Autoregressive Entropy Models for Learned Image Compression , 2020, 2020 IEEE International Conference on Image Processing (ICIP).

[35]  Inbar Mosseri,et al.  XGAN: Unsupervised Image-to-Image Translation for many-to-many Mappings , 2017, Domain Adaptation for Visual Understanding.

[36]  Luc Van Gool,et al.  Conditional Probability Models for Deep Image Compression , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[37]  Luca Benini,et al.  Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representations , 2017, NIPS.

[38]  David Minnen,et al.  Full Resolution Image Compression with Recurrent Neural Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[39]  David Minnen,et al.  Joint Autoregressive and Hierarchical Priors for Learned Image Compression , 2018, NeurIPS.