mlsanityData to 7 Oct 2026

pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis

arXiv 2012.00926 ↗First posted 2 Dec 2020cs.CV cs.GRcited by 708

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Cited by 89 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

We have witnessed rapid progress on 3D-aware image synthesis, leveraging recent advances in generative visual models and neural rendering. Existing approaches however fall short in two ways: first, they may lack an underlying 3D representation or rely on view-inconsistent rendering, hence synthesizing images that are not multi-view consistent; second, they often depend upon representation network architectures that are not expressive enough, and their results thus lack in image quality. We propose a novel generative model, named Periodic Implicit Generative Adversarial Networks (π-GAN or pi-GAN), for high-quality 3D-aware image synthesis. π-GAN leverages neural representations with periodic activation functions and volumetric rendering to represent scenes as view-consistent 3D representations with fine detail. The proposed approach obtains state-of-the-art results for 3D-aware image synthesis with multiple real and synthetic datasets.

Key facts. Cited by 708 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Dec 2020.

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Citing papers per year: 2021: 74; 2022: 178; 2023: 245; 2024: 130; 2025: 56; 2026: 25.

708 papers.

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  1. 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,006
  2. 2021Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fieldscited by 1,957
  3. 2022Magic3D: High-Resolution Text-to-3D Content Creationcited by 1,285
  4. 2022TensoRF: Tensorial Radiance Fieldscited by 1,275
  5. 2021Efficient Geometry-aware 3D Generative Adversarial Networkscited by 1,204
  6. 2021Direct Voxel Grid Optimization: Super-fast Convergence for Radiance Fields Reconstructioncited by 961
  7. 2021Depth-supervised NeRF: Fewer Views and Faster Training for Freecited by 732
  8. 2022Point-E: A System for Generating 3D Point Clouds from Complex Promptscited by 694
  9. 2021KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPscited by 672
  10. 2021RegNeRF: Regularizing Neural Radiance Fields for View Synthesis from Sparse Inputscited by 614
  11. 2022Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generationcited by 597
  12. 2021NICE-SLAM: Neural Implicit Scalable Encoding for SLAMcited by 586
38 more
  1. 2023HexPlane: A Fast Representation for Dynamic Scenescited by 582
  2. 2022LION: Latent Point Diffusion Models for 3D Shape Generationcited by 552
  3. 2021Neural Fields in Visual Computing and Beyondcited by 539
  4. 2021Zero-Shot Text-Guided Object Generation with Dream Fieldscited by 513
  5. 2022Latent-NeRF for Shape-Guided Generation of 3D Shapes and Texturescited by 506
  6. 2022Point-NeRF: Point-based Neural Radiance Fieldscited by 503
  7. 2021StyleNeRF: A Style-based 3D-Aware Generator for High-resolution Image Synthesiscited by 477
  8. 2021Baking Neural Radiance Fields for Real-Time View Synthesiscited by 465
  9. 2022GET3D: A Generative Model of High Quality 3D Textured Shapes Learned from Imagescited by 446
  10. 2023LangSplat: 3D Language Gaussian Splattingcited by 410
  11. 2021CLIP-NeRF: Text-and-Image Driven Manipulation of Neural Radiance Fieldscited by 369
  12. 2021GAN Inversion: A Surveycited by 366
  13. 2021Advances in Neural Renderingcited by 365
  14. 2021Light Field Networks: Neural Scene Representations with Single-Evaluation Renderingcited by 330
  15. 2023OmniObject3D: Large-Vocabulary 3D Object Dataset for Realistic Perception, Reconstruction and Generationcited by 324
  16. 2023ReconFusion: 3D Reconstruction with Diffusion Priorscited by 317
  17. 2021Neural RGB-D Surface Reconstructioncited by 312
  18. 2022Rodin: A Generative Model for Sculpting 3D Digital Avatars Using Diffusioncited by 309
  19. 2021StyleGAN-V: A Continuous Video Generator with the Price, Image Quality and Perks of StyleGAN2cited by 300
  20. 2024GRM: Large Gaussian Reconstruction Model for Efficient 3D Reconstruction and Generationcited by 298
  21. 2021StyleSDF: High-Resolution 3D-Consistent Image and Geometry Generationcited by 289
  22. 2022SDFusion: Multimodal 3D Shape Completion, Reconstruction, and Generationcited by 287
  23. 2023FSGS: Real-Time Few-shot View Synthesis using Gaussian Splattingcited by 278
  24. 20223D Neural Field Generation using Triplane Diffusioncited by 274
  25. 2023Generative Novel View Synthesis with 3D-Aware Diffusion Modelscited by 273
  26. 2022CelebV-HQ: A Large-Scale Video Facial Attributes Datasetcited by 246
  27. 2022NeuMan: Neural Human Radiance Field from a Single Videocited by 244
  28. 2022Panoptic Neural Fields: A Semantic Object-Aware Neural Scene Representationcited by 243
  29. 2023DreamBooth3D: Subject-Driven Text-to-3D Generationcited by 235
  30. 2023Text2Tex: Text-driven Texture Synthesis via Diffusion Modelscited by 234
  31. 2021DONeRF: Towards Real-Time Rendering of Compact Neural Radiance Fields using Depth Oracle Networkscited by 232
  32. 2021I M Avatar: Implicit Morphable Head Avatars from Videoscited by 230
  33. 2021HeadNeRF: A Real-time NeRF-based Parametric Head Modelcited by 228
  34. 2023LucidDreamer: Domain-free Generation of 3D Gaussian Splatting Scenescited by 228
  35. 2021Editing Conditional Radiance Fieldscited by 222
  36. 2023GS-IR: 3D Gaussian Splatting for Inverse Renderingcited by 220
  37. 2023Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifoldcited by 218
  38. 2022Tensor4D : Efficient Neural 4D Decomposition for High-fidelity Dynamic Reconstruction and Renderingcited by 217

50 most cited of 708 All 708 (JSON)