mlsanityData to 7 Oct 2026

Transforming and Projecting Images into Class-conditional Generative Networks

arXiv 2005.01703 ↗First posted 4 May 2020cs.CVcited by 76

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Abstract (arXiv)

We present a method for projecting an input image into the space of a class-conditional generative neural network. We propose a method that optimizes for transformation to counteract the model biases in generative neural networks. Specifically, we demonstrate that one can solve for image translation, scale, and global color transformation, during the projection optimization to address the object-center bias and color bias of a Generative Adversarial Network. This projection process poses a difficult optimization problem, and purely gradient-based optimizations fail to find good solutions. We describe a hybrid optimization strategy that finds good projections by estimating transformations and class parameters. We show the effectiveness of our method on real images and further demonstrate how the corresponding projections lead to better editability of these images.

Key facts. Cited by 76 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 May 2020.

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Citing papers per year: 2021: 24; 2022: 20; 2023: 23; 2024: 9.

76 papers.

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  1. 2021SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equationscited by 1,903
  2. 2021DiffusionCLIP: Text-Guided Diffusion Models for Robust Image Manipulationcited by 640
  3. 2021ILVR: Conditioning Method for Denoising Diffusion Probabilistic Modelscited by 634
  4. 2023Zero-shot Image-to-Image Translationcited by 503
  5. 2021GAN Inversion: A Surveycited by 366
  6. 2024Shape of Motion: 4D Reconstruction from a Single Videocited by 247
  7. 2022Monocular Dynamic View Synthesis: A Reality Checkcited by 199
  8. 2021High-Fidelity GAN Inversion for Image Attribute Editingcited by 197
  9. 2021EditGAN: High-Precision Semantic Image Editingcited by 156
  10. 2021Semantic Segmentation with Generative Models: Semi-Supervised Learning and Strong Out-of-Domain Generalizationcited by 141
  11. 2023Generalizing Dataset Distillation via Deep Generative Priorcited by 125
  12. 2021Paint by Wordcited by 107
38 more
  1. 2021Regularizing Generative Adversarial Networks under Limited Datacited by 105
  2. 2021Exploiting Spatial Dimensions of Latent in GAN for Real-time Image Editingcited by 91
  3. 2022Auditing Privacy Defenses in Federated Learning via Generative Gradient Leakagecited by 72
  4. 2022Any-resolution Training for High-resolution Image Synthesiscited by 72
  5. 2021FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space Optimizationcited by 71
  6. 2022High-fidelity 3D GAN Inversion by Pseudo-multi-view Optimizationcited by 65
  7. 2021GAN-Supervised Dense Visual Alignmentcited by 61
  8. 2021Using latent space regression to analyze and leverage compositionality in GANscited by 55
  9. 2021GAN Inversion for Out-of-Range Images with Geometric Transformationscited by 55
  10. 2021Anycost GANs for Interactive Image Synthesis and Editingcited by 54
  11. 2021Ensembling with Deep Generative Viewscited by 53
  12. 2021StyleVideoGAN: A Temporal Generative Model using a Pretrained StyleGANcited by 47
  13. 2022Deep Equilibrium Approaches to Diffusion Modelscited by 42
  14. 2022Spatially-Adaptive Multilayer Selection for GAN Inversion and Editingcited by 39
  15. 2021Sketch Your Own GANcited by 37
  16. 2022Diagnosing and Fixing Manifold Overfitting in Deep Generative Modelscited by 28
  17. 2022Temporally Consistent Semantic Video Editingcited by 28
  18. 2022Generative Visual Prompt: Unifying Distributional Control of Pre-Trained Generative Modelscited by 27
  19. 2021Towards Open-World Text-Guided Face Image Generation and Manipulationcited by 25
  20. 2022Rewriting Geometric Rules of a GANcited by 25
  21. 2022High-fidelity GAN Inversion with Padding Spacecited by 23
  22. 2023Boundary Guided Learning-Free Semantic Control with Diffusion Modelscited by 23
  23. 2023Attributing Image Generative Models using Latent Fingerprintscited by 20
  24. 2021Toward Spatially Unbiased Generative Modelscited by 17
  25. 2022Feature-Style Encoder for Style-Based GAN Inversioncited by 15
  26. 2022Landscape Learning for Neural Network Inversioncited by 15
  27. 2022PetsGAN: Rethinking Priors for Single Image Generationcited by 14
  28. 20233D-aware Blending with Generative NeRFscited by 13
  29. 2021ExSinGAN: Learning an Explainable Generative Model from a Single Imagecited by 12
  30. 2024Inversion-based Latent Bayesian Optimizationcited by 11
  31. 2023Learning to Evaluate the Artness of AI-generated Imagescited by 10
  32. 2023Make It So: Steering StyleGAN for Any Image Inversion and Editingcited by 9
  33. 2022Controllable Evaluation and Generation of Physical Adversarial Patch on Face Recognitioncited by 8
  34. 2023NaviNeRF: NeRF-based 3D Representation Disentanglement by Latent Semantic Navigationcited by 8
  35. 2022Cycle Encoding of a StyleGAN Encoder for Improved Reconstruction and Editabilitycited by 7
  36. 2023Instance-Conditioned GAN Data Augmentation for Representation Learningcited by 7
  37. 2023Stable Attribute Group Editing for Reliable Few-shot Image Generationcited by 6
  38. 2023Progressive Text-to-Image Diffusion with Soft Latent Directioncited by 6

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