mlsanityData to 7 Oct 2026

AutoGAN: Neural Architecture Search for Generative Adversarial Networks

arXiv 1908.03835 ↗First posted 11 Aug 2019cs.CV cs.LG eess.IVcited by 94

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Abstract (arXiv)

Neural architecture search (NAS) has witnessed prevailing success in image classification and (very recently) segmentation tasks. In this paper, we present the first preliminary study on introducing the NAS algorithm to generative adversarial networks (GANs), dubbed AutoGAN. The marriage of NAS and GANs faces its unique challenges. We define the search space for the generator architectural variations and use an RNN controller to guide the search, with parameter sharing and dynamic-resetting to accelerate the process. Inception score is adopted as the reward, and a multi-level search strategy is introduced to perform NAS in a progressive way. Experiments validate the effectiveness of AutoGAN on the task of unconditional image generation. Specifically, our discovered architectures achieve highly competitive performance compared to current state-of-the-art hand-crafted GANs, e.g., setting new state-of-the-art FID scores of 12.42 on CIFAR-10, and 31.01 on STL-10, respectively. We also conclude with a discussion of the current limitations and future potential of AutoGAN. The code is available at https://github.com/TAMU-VITA/AutoGAN

Key facts. Cited by 94 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Aug 2019.

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Citing papers per year: 2021: 37; 2022: 18; 2023: 26; 2024: 8; 2025: 2; 2026: 3.

94 papers.

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  11. 2023DiffiT: Diffusion Vision Transformers for Image Generationcited by 104
  12. 2021Fourier Space Losses for Efficient Perceptual Image Super-Resolutioncited by 72
38 more
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  3. 2023ZiCo: Zero-shot NAS via Inverse Coefficient of Variation on Gradientscited by 57
  4. 2022Neural Architecture Search for Spiking Neural Networkscited by 52
  5. 2022Truncated Diffusion Probabilistic Models and Diffusion-based Adversarial Auto-Encoderscited by 42
  6. 2023Generative Modeling through the Semi-dual Formulation of Unbalanced Optimal Transportcited by 39
  7. 2021GANs Can Play Lottery Tickets Toocited by 32
  8. 2025D3: Training-Free AI-Generated Video Detection Using Second-Order Featurescited by 32
  9. 2022Learning to Generate Realistic Noisy Images via Pixel-level Noise-aware Adversarial Trainingcited by 29
  10. 2021Styleformer: Transformer based Generative Adversarial Networks with Style Vectorcited by 27
  11. 2021Data-Efficient GAN Training Beyond (Just) Augmentations: A Lottery Ticket Perspectivecited by 25
  12. 2021Gradient Normalization for Generative Adversarial Networkscited by 25
  13. 2021Online Multi-Granularity Distillation for GAN Compressioncited by 24
  14. 2022RFormer: Transformer-based Generative Adversarial Network for Real Fundus Image Restoration on A New Clinical Benchmarkcited by 24
  15. 2024Scalable Wasserstein Gradient Flow for Generative Modeling through Unbalanced Optimal Transportcited by 22
  16. 2023Zero-Shot Neural Architecture Search: Challenges, Solutions, and Opportunitiescited by 21
  17. 2021WAS-VTON: Warping Architecture Search for Virtual Try-on Networkcited by 18
  18. 2024ClassDiffusion: More Aligned Personalization Tuning with Explicit Class Guidancecited by 18
  19. 2023PAIR-Diffusion: A Comprehensive Multimodal Object-Level Image Editorcited by 17
  20. 2021Trilevel Neural Architecture Search for Efficient Single Image Super-Resolutioncited by 15
  21. 2021MFAGAN: A Compression Framework for Memory-Efficient On-Device Super-Resolution GANcited by 14
  22. 2022GhostNets on Heterogeneous Devices via Cheap Operationscited by 14
  23. 2023Catch-Up Distillation: You Only Need to Train Once for Accelerating Samplingcited by 13
  24. 2022Fast-Vid2Vid: Spatial-Temporal Compression for Video-to-Video Synthesiscited by 12
  25. 2021T-AutoML: Automated Machine Learning for Lesion Segmentation using Transformers in 3D Medical Imagingcited by 11
  26. 2021Partition-Guided GANscited by 9
  27. 2021RANK-NOSH: Efficient Predictor-Based Architecture Search via Non-Uniform Successive Halvingcited by 9
  28. 2022Bi-level Alignment for Cross-Domain Crowd Countingcited by 8
  29. 2023Analyzing and Improving Optimal-Transport-based Adversarial Networkscited by 8
  30. 2021Sandwich Batch Normalization: A Drop-In Replacement for Feature Distribution Heterogeneitycited by 7
  31. 2021Understanding and Accelerating Neural Architecture Search with Training-Free and Theory-Grounded Metricscited by 7
  32. 2022Generator Knows What Discriminator Should Learn in Unconditional GANscited by 7
  33. 2023Restoration based Generative Modelscited by 6
  34. 2023EGANS: Evolutionary Generative Adversarial Network Search for Zero-Shot Learningcited by 6
  35. 2023SMaRt: Improving GANs with Score Matching Regularitycited by 6
  36. 2021Contrastive Self-supervised Neural Architecture Searchcited by 5
  37. 2021Combining Transformer Generators with Convolutional Discriminatorscited by 5
  38. 2021Dynamically Grown Generative Adversarial Networkscited by 5

50 most cited of 94 All 94 (JSON)