AttrLostGAN: Attribute Controlled Image Synthesis from Reconfigurable Layout and Style

[1]  Stefan Wermter,et al.  Semantic Object Accuracy for Generative Text-to-Image Synthesis , 2019, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Andreas Dengel,et al.  Adversarial Text-to-Image Synthesis: A Review , 2021, Neural Networks.

[3]  Tianfu Wu,et al.  Learning Layout and Style Reconfigurable GANs for Controllable Image Synthesis , 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  R Devon Hjelm,et al.  Object-Centric Image Generation from Layouts , 2020, AAAI.

[5]  Michal Drozdzal,et al.  Generating unseen complex scenes: are we there yet? , 2020, ArXiv.

[6]  Bo Zhao,et al.  Attribute-Guided Image Generation from Layout , 2020, BMVC.

[7]  Jihua Zhu,et al.  S2IGAN: Speech-to-Image Generation via Adversarial Learning , 2020, INTERSPEECH.

[8]  Kyogu Lee,et al.  From Inference to Generation: End-to-end Fully Self-supervised Generation of Human Face from Speech , 2020, ICLR.

[9]  Trevor Darrell,et al.  Learning Canonical Representations for Scene Graph to Image Generation , 2019, ECCV.

[10]  Thomas Lukasiewicz,et al.  ManiGAN: Text-Guided Image Manipulation , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[11]  Thomas Hofmann,et al.  Controlling Style and Semantics in Weakly-Supervised Image Generation , 2019, ECCV.

[12]  Oron Ashual,et al.  Specifying Object Attributes and Relations in Interactive Scene Generation , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[13]  Philip H. S. Torr,et al.  Controllable Text-to-Image Generation , 2019, NeurIPS.

[14]  Wei Sun,et al.  Image Synthesis From Reconfigurable Layout and Style , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[15]  Ali Razavi,et al.  Generating Diverse High-Fidelity Images with VQ-VAE-2 , 2019, NeurIPS.

[16]  Suman V. Ravuri,et al.  Classification Accuracy Score for Conditional Generative Models , 2019, NeurIPS.

[17]  Xiaogang Wang,et al.  PasteGAN: A Semi-Parametric Method to Generate Image from Scene Graph , 2019, NeurIPS.

[18]  Jiachen Li,et al.  Text Guided Person Image Synthesis , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[19]  Wei Chen,et al.  DM-GAN: Dynamic Memory Generative Adversarial Networks for Text-To-Image Synthesis , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[20]  Lei Zhang,et al.  Object-Driven Text-To-Image Synthesis via Adversarial Training , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[21]  Stefan Wermter,et al.  Generating Multiple Objects at Spatially Distinct Locations , 2019, ICLR.

[22]  Timo Aila,et al.  A Style-Based Generator Architecture for Generative Adversarial Networks , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[23]  Bo Zhao,et al.  Image Generation From Layout , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[24]  Jeff Donahue,et al.  Large Scale GAN Training for High Fidelity Natural Image Synthesis , 2018, ICLR.

[25]  Ali Borji,et al.  Pros and Cons of GAN Evaluation Measures , 2018, Comput. Vis. Image Underst..

[26]  Xiaogang Wang,et al.  StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[27]  Seonghyeon Nam,et al.  Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language , 2018, NeurIPS.

[28]  Li Fei-Fei,et al.  Image Generation from Scene Graphs , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[29]  Takeru Miyato,et al.  cGANs with Projection Discriminator , 2018, ICLR.

[30]  Seunghoon Hong,et al.  Inferring Semantic Layout for Hierarchical Text-to-Image Synthesis , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[31]  Alexei A. Efros,et al.  The Unreasonable Effectiveness of Deep Features as a Perceptual Metric , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[32]  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.

[33]  Jung-Woo Ha,et al.  StarGAN: Unified Generative Adversarial Networks for Multi-domain Image-to-Image Translation , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[34]  Harshad Rai,et al.  Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks , 2018 .

[35]  Bohyung Han,et al.  Visual Reference Resolution using Attention Memory for Visual Dialog , 2017, NIPS.

[36]  Yike Guo,et al.  Semantic Image Synthesis via Adversarial Learning , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

[37]  Sepp Hochreiter,et al.  GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium , 2017, NIPS.

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

[39]  Jonathon Shlens,et al.  Conditional Image Synthesis with Auxiliary Classifier GANs , 2016, ICML.

[40]  Aykut Erdem,et al.  Learning to Generate Images of Outdoor Scenes from Attributes and Semantic Layouts , 2016, ArXiv.

[41]  Wojciech Zaremba,et al.  Improved Techniques for Training GANs , 2016, NIPS.

[42]  Bernt Schiele,et al.  Generative Adversarial Text to Image Synthesis , 2016, ICML.

[43]  Michael S. Bernstein,et al.  Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations , 2016, International Journal of Computer Vision.

[44]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[45]  Honglak Lee,et al.  Attribute2Image: Conditional Image Generation from Visual Attributes , 2015, ECCV.

[46]  Matthias Bethge,et al.  A note on the evaluation of generative models , 2015, ICLR.

[47]  Joan Bruna,et al.  Deep Convolutional Networks on Graph-Structured Data , 2015, ArXiv.

[48]  Sergey Ioffe,et al.  Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.

[49]  Yoshua Bengio,et al.  Generative Adversarial Nets , 2014, NIPS.

[50]  Simon Osindero,et al.  Conditional Generative Adversarial Nets , 2014, ArXiv.

[51]  Max Welling,et al.  Auto-Encoding Variational Bayes , 2013, ICLR.