mlsanityData to 7 Oct 2026

SynSin: End-to-end View Synthesis from a Single Image

arXiv 1912.08804 ↗First posted 18 Dec 2019cs.CVcited by 364

Not on the map. Why?

Cited by 29 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Single image view synthesis allows for the generation of new views of a scene given a single input image. This is challenging, as it requires comprehensively understanding the 3D scene from a single image. As a result, current methods typically use multiple images, train on ground-truth depth, or are limited to synthetic data. We propose a novel end-to-end model for this task; it is trained on real images without any ground-truth 3D information. To this end, we introduce a novel differentiable point cloud renderer that is used to transform a latent 3D point cloud of features into the target view. The projected features are decoded by our refinement network to inpaint missing regions and generate a realistic output image. The 3D component inside of our generative model allows for interpretable manipulation of the latent feature space at test time, e.g. we can animate trajectories from a single image. Unlike prior work, we can generate high resolution images and generalise to other input resolutions. We outperform baselines and prior work on the Matterport, Replica, and RealEstate10K datasets.

Key facts. Cited by 364 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Dec 2019.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 60; 2022: 64; 2023: 91; 2024: 79; 2025: 51; 2026: 19.

364 papers.

Sort:

By area:

  1. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,141
  2. 2021Plenoxels: Radiance Fields without Neural Networkscited by 1,607
  3. 2023DUSt3R: Geometric 3D Vision Made Easycited by 1,526
  4. 20242D Gaussian Splatting for Geometrically Accurate Radiance Fieldscited by 1,061
  5. 2021Depth-supervised NeRF: Fewer Views and Faster Training for Freecited by 732
  6. 2023Scaffold-GS: Structured 3D Gaussians for View-Adaptive Renderingcited by 684
  7. 2023pixelSplat: 3D Gaussian Splats from Image Pairs for Scalable Generalizable 3D Reconstructioncited by 668
  8. 2023Mip-Splatting: Alias-free 3D Gaussian Splattingcited by 661
  9. 2021Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstructioncited by 646
  10. 2021BARF: Bundle-Adjusting Neural Radiance Fieldscited by 641
  11. 2022Point-NeRF: Point-based Neural Radiance Fieldscited by 503
  12. 2023Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectivescited by 477
38 more
  1. 2021Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesiscited by 464
  2. 2021Dynamic View Synthesis from Dynamic Monocular Videocited by 420
  3. 2024ViewCrafter: Taming Video Diffusion Models for High-fidelity Novel View Synthesiscited by 392
  4. 2021Advances in Neural Renderingcited by 365
  5. 2023Compact 3D Gaussian Representation for Radiance Fieldcited by 365
  6. 2023Splatter Image: Ultra-Fast Single-View 3D Reconstructioncited by 359
  7. 2024GS-LRM: Large Reconstruction Model for 3D Gaussian Splattingcited by 344
  8. 2023Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Priorcited by 341
  9. 2023Spacetime Gaussian Feature Splatting for Real-Time Dynamic View Synthesiscited by 341
  10. 2021Mixture of Volumetric Primitives for Efficient Neural Renderingcited by 277
  11. 2023Generative Novel View Synthesis with 3D-Aware Diffusion Modelscited by 273
  12. 2023Text2Room: Extracting Textured 3D Meshes from 2D Text-to-Image Modelscited by 245
  13. 2021A-NeRF: Articulated Neural Radiance Fields for Learning Human Shape, Appearance, and Posecited by 233
  14. 2024A Survey on 3D Gaussian Splattingcited by 221
  15. 2021NeX: Real-time View Synthesis with Neural Basis Expansioncited by 215
  16. 2024WonderWorld: Interactive 3D Scene Generation from a Single Imagecited by 197
  17. 2023Robust Dynamic Radiance Fieldscited by 193
  18. 2023GaussianAvatar: Towards Realistic Human Avatar Modeling from a Single Video via Animatable 3D Gaussianscited by 190
  19. 2024CityGaussian: Real-time High-quality Large-Scale Scene Rendering with Gaussianscited by 190
  20. 2021Point-Based Neural Rendering with Per-View Optimizationcited by 188
  21. 2022PointAvatar: Deformable Point-based Head Avatars from Videoscited by 183
  22. 2023NerfDiff: Single-image View Synthesis with NeRF-guided Distillation from 3D-aware Diffusioncited by 179
  23. 2023Depth-Regularized Optimization for 3D Gaussian Splatting in Few-Shot Imagescited by 172
  24. 2023GPS-Gaussian: Generalizable Pixel-wise 3D Gaussian Splatting for Real-time Human Novel View Synthesiscited by 170
  25. 2023GauHuman: Articulated Gaussian Splatting from Monocular Human Videoscited by 168
  26. 2023SceneScape: Text-Driven Consistent Scene Generationcited by 160
  27. 2023PoseDiffusion: Solving Pose Estimation via Diffusion-aided Bundle Adjustmentcited by 146
  28. 2022SelfRecon: Self Reconstruction Your Digital Avatar from Monocular Videocited by 144
  29. 2022StylizedNeRF: Consistent 3D Scene Stylization as Stylized NeRF via 2D-3D Mutual Learningcited by 140
  30. 2021MINE: Towards Continuous Depth MPI with NeRF for Novel View Synthesiscited by 133
  31. 2023SelfOcc: Self-Supervised Vision-Based 3D Occupancy Predictioncited by 133
  32. 2021Hallucinated Neural Radiance Fields in the Wildcited by 130
  33. 2023Text2NeRF: Text-Driven 3D Scene Generation with Neural Radiance Fieldscited by 122
  34. 2022Generalizable Patch-Based Neural Renderingcited by 121
  35. 2021Pathdreamer: A World Model for Indoor Navigationcited by 117
  36. 2023Consistent View Synthesis with Pose-Guided Diffusion Modelscited by 117
  37. 2023The Surprising Effectiveness of Diffusion Models for Optical Flow and Monocular Depth Estimationcited by 116
  38. 2024latentSplat: Autoencoding Variational Gaussians for Fast Generalizable 3D Reconstructioncited by 114

50 most cited of 364 All 364 (JSON)