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Neural Photo Editing with Introspective Adversarial Networks

arXiv 1609.07093 ↗First posted 22 Sep 2016cs.LG cs.CV cs.NEcited by 109

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Abstract (arXiv)

The increasingly photorealistic sample quality of generative image models suggests their feasibility in applications beyond image generation. We present the Neural Photo Editor, an interface that leverages the power of generative neural networks to make large, semantically coherent changes to existing images. To tackle the challenge of achieving accurate reconstructions without loss of feature quality, we introduce the Introspective Adversarial Network, a novel hybridization of the VAE and GAN. Our model efficiently captures long-range dependencies through use of a computational block based on weight-shared dilated convolutions, and improves generalization performance with Orthogonal Regularization, a novel weight regularization method. We validate our contributions on CelebA, SVHN, and CIFAR-100, and produce samples and reconstructions with high visual fidelity.

Key facts. Cited by 109 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Sep 2016.

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Citing papers per year: 2021: 38; 2022: 17; 2023: 26; 2024: 17; 2025: 9; 2026: 2.

109 papers.

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  1. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  2. 2022Generative Adversarial Networkscited by 5,603
  3. 2021SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equationscited by 1,903
  4. 2021ILVR: Conditioning Method for Denoising Diffusion Probabilistic Modelscited by 634
  5. 2023Scaling up GANs for Text-to-Image Synthesiscited by 492
  6. 2023Text-to-image Diffusion Models in Generative AI: A Surveycited by 264
  7. 2021Editing Conditional Radiance Fieldscited by 222
  8. 2021EditGAN: High-Precision Semantic Image Editingcited by 156
  9. 2021Semantic Segmentation with Generative Models: Semi-Supervised Learning and Strong Out-of-Domain Generalizationcited by 141
  10. 2023Generalizing Dataset Distillation via Deep Generative Priorcited by 125
  11. 2021Talk-to-Edit: Fine-Grained Facial Editing via Dialogcited by 102
  12. 2021D2C: Diffusion-Denoising Models for Few-shot Conditional Generationcited by 96
38 more
  1. 2021Exploiting Spatial Dimensions of Latent in GAN for Real-time Image Editingcited by 91
  2. 2023Stay on topic with Classifier-Free Guidancecited by 90
  3. 2022Synthetic Data -- what, why and how?cited by 66
  4. 2021GAN-Supervised Dense Visual Alignmentcited by 61
  5. 2023LayoutDM: Transformer-based Diffusion Model for Layout Generationcited by 57
  6. 2021In&Out : Diverse Image Outpainting via GAN Inversioncited by 55
  7. 2021Anycost GANs for Interactive Image Synthesis and Editingcited by 54
  8. 2021Ensembling with Deep Generative Viewscited by 53
  9. 2022UniTune: Text-Driven Image Editing by Fine Tuning a Diffusion Model on a Single Imagecited by 42
  10. 2022Spatially-Adaptive Multilayer Selection for GAN Inversion and Editingcited by 39
  11. 2022StudioGAN: A Taxonomy and Benchmark of GANs for Image Synthesiscited by 38
  12. 2021Learning with Hyperspherical Uniformitycited by 35
  13. 2021Orthogonal Jacobian Regularization for Unsupervised Disentanglement in Image Generationcited by 35
  14. 2024Copyright Protection in Generative AI: A Technical Perspectivecited by 35
  15. 2023HetGPT: Harnessing the Power of Prompt Tuning in Pre-Trained Heterogeneous Graph Neural Networkscited by 32
  16. 2024Conditional Image Synthesis with Diffusion Models: A Surveycited by 29
  17. 2021Conditional Generative Models for Counterfactual Explanationscited by 28
  18. 2021Verification of Image-based Neural Network Controllers Using Generative Modelscited by 27
  19. 2021Unsupervised Foreground Extraction via Deep Region Competitioncited by 26
  20. 2023CUDA: Convolution-based Unlearnable Datasetscited by 26
  21. 2021Linear Semantics in Generative Adversarial Networkscited by 25
  22. 2021Gradient Normalization for Generative Adversarial Networkscited by 25
  23. 2024Revisiting Non-Autoregressive Transformers for Efficient Image Synthesiscited by 22
  24. 2024ODICE: Revealing the Mystery of Distribution Correction Estimation via Orthogonal-gradient Updatecited by 21
  25. 2024Unlocking Dataset Distillation with Diffusion Modelscited by 21
  26. 2021Towards Deeper Deep Reinforcement Learning with Spectral Normalizationcited by 19
  27. 2022Avocodo: Generative Adversarial Network for Artifact-free Vocodercited by 18
  28. 2022Tele-Knowledge Pre-training for Fault Analysiscited by 18
  29. 2021Toward Spatially Unbiased Generative Modelscited by 17
  30. 2021Wasserstein Generative Adversarial Uncertainty Quantification in Physics-Informed Neural Networkscited by 16
  31. 2023Adversarial Score Distillation: When score distillation meets GANcited by 15
  32. 2024Learn to Preserve and Diversify: Parameter-Efficient Group with Orthogonal Regularization for Domain Generalizationcited by 14
  33. 2024Hierarchical Features Matter: A Deep Exploration of Progressive Parameterization Method for Dataset Distillationcited by 13
  34. 2021ExSinGAN: Learning an Explainable Generative Model from a Single Imagecited by 12
  35. 2024Text-centric Alignment for Multi-Modality Learningcited by 12
  36. 2021Comparison and Analysis of Image-to-Image Generative Adversarial Networks: A Surveycited by 11
  37. 2021Learning cortical representations through perturbed and adversarial dreamingcited by 10
  38. 2021StyleCariGAN: Caricature Generation via StyleGAN Feature Map Modulationcited by 9

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