mlsanityData to 7 Oct 2026

Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks

arXiv 1506.05751 ↗First posted 18 Jun 2015cs.CVcited by 214

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Cited by 24 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

In this paper we introduce a generative parametric model capable of producing high quality samples of natural images. Our approach uses a cascade of convolutional networks within a Laplacian pyramid framework to generate images in a coarse-to-fine fashion. At each level of the pyramid, a separate generative convnet model is trained using the Generative Adversarial Nets (GAN) approach (Goodfellow et al.). Samples drawn from our model are of significantly higher quality than alternate approaches. In a quantitative assessment by human evaluators, our CIFAR10 samples were mistaken for real images around 40% of the time, compared to 10% for samples drawn from a GAN baseline model. We also show samples from models trained on the higher resolution images of the LSUN scene dataset.

Key facts. Cited by 214 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Jun 2015.

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Citing papers per year: 2020: 1; 2021: 67; 2022: 47; 2023: 40; 2024: 24; 2025: 24; 2026: 11.

214 papers.

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  2. 2022Generative Adversarial Networkscited by 5,603
  3. 2021Image Super-Resolution via Iterative Refinementcited by 1,506
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  8. 2023Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion modelscited by 199
  9. 2023VIEScore: Towards Explainable Metrics for Conditional Image Synthesis Evaluationcited by 196
  10. 2021PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learningcited by 181
  11. 2022Graph neural networks for materials science and chemistrycited by 181
  12. 2022Generative Modelling With Inverse Heat Dissipationcited by 164
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  3. 2021Pros and Cons of GAN Evaluation Measures: New Developmentscited by 121
  4. 2022Deep Image Deblurring: A Surveycited by 94
  5. 2022An Introduction to Neural Data Compressioncited by 78
  6. 2023ImagenHub: Standardizing the evaluation of conditional image generation modelscited by 75
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  8. 2023Matryoshka Diffusion Modelscited by 70
  9. 2021High-Resolution Photorealistic Image Translation in Real-Time: A Laplacian Pyramid Translation Networkcited by 61
  10. 2021Reverse Engineering of Generative Models: Inferring Model Hyperparameters from Generated Imagescited by 58
  11. 2025DeCo: Frequency-Decoupled Pixel Diffusion for End-to-End Image Generationcited by 55
  12. 2021Ensembling with Deep Generative Viewscited by 53
  13. 2021On Aliased Resizing and Surprising Subtleties in GAN Evaluationcited by 51
  14. 2023RenAIssance: A Survey into AI Text-to-Image Generation in the Era of Large Modelcited by 47
  15. 2021Drafting and Revision: Laplacian Pyramid Network for Fast High-Quality Artistic Style Transfercited by 41
  16. 2022Recent Advances for Quantum Neural Networks in Generative Learningcited by 39
  17. 2022A Unified Pyramid Recurrent Network for Video Frame Interpolationcited by 39
  18. 2022StudioGAN: A Taxonomy and Benchmark of GANs for Image Synthesiscited by 38
  19. 2022BlobGAN: Spatially Disentangled Scene Representationscited by 35
  20. 2021EigenGAN: Layer-Wise Eigen-Learning for GANscited by 34
  21. 2024A survey of synthetic data augmentation methods in computer visioncited by 34
  22. 2024Posterior-Mean Rectified Flow: Towards Minimum MSE Photo-Realistic Image Restorationcited by 32
  23. 2024On the Challenges and Opportunities in Generative AIcited by 31
  24. 2021PhotoWCT2: Compact Autoencoder for Photorealistic Style Transfer Resulting from Blockwise Training and Skip Connections of High-Frequency Residualscited by 30
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  26. 2021VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision Transformerscited by 28
  27. 2022TabSynDex: A Universal Metric for Robust Evaluation of Synthetic Tabular Datacited by 27
  28. 2022Generative Modeling in Sinogram Domain for Sparse-view CT Reconstructioncited by 27
  29. 2021Data-Efficient GAN Training Beyond (Just) Augmentations: A Lottery Ticket Perspectivecited by 25
  30. 2021Linear Semantics in Generative Adversarial Networkscited by 25
  31. 2023A Comprehensive Overview and Comparative Analysis on Deep Learning Models: CNN, RNN, LSTM, GRUcited by 25
  32. 2021Improving GAN Equilibrium by Raising Spatial Awarenesscited by 22
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  36. 2020Biased Mixtures Of Experts: Enabling Computer Vision Inference Under Data Transfer Limitationscited by 20
  37. 2021Improving Visual Quality of Image Synthesis by A Token-based Generator with Transformerscited by 19
  38. 2023ADDP: Learning General Representations for Image Recognition and Generation with Alternating Denoising Diffusion Processcited by 19

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