mlsanityData to 7 Oct 2026

One Shot 3D Photography

arXiv 2008.12298 ↗First posted 27 Aug 2020cs.CV cs.GRcited by 45

Not on the map. Why?

Abstract (arXiv)

3D photography is a new medium that allows viewers to more fully experience a captured moment. In this work, we refer to a 3D photo as one that displays parallax induced by moving the viewpoint (as opposed to a stereo pair with a fixed viewpoint). 3D photos are static in time, like traditional photos, but are displayed with interactive parallax on mobile or desktop screens, as well as on Virtual Reality devices, where viewing it also includes stereo. We present an end-to-end system for creating and viewing 3D photos, and the algorithmic and design choices therein. Our 3D photos are captured in a single shot and processed directly on a mobile device. The method starts by estimating depth from the 2D input image using a new monocular depth estimation network that is optimized for mobile devices. It performs competitively to the state-of-the-art, but has lower latency and peak memory consumption and uses an order of magnitude fewer parameters. The resulting depth is lifted to a layered depth image, and new geometry is synthesized in parallax regions. We synthesize color texture and structures in the parallax regions as well, using an inpainting network, also optimized for mobile devices, on the LDI directly. Finally, we convert the result into a mesh-based representation that can be efficiently transmitted and rendered even on low-end devices and over poor network connections. Altogether, the processing takes just a few seconds on a mobile device, and the result can be instantly viewed and shared. We perform extensive quantitative evaluation to validate our system and compare its new components against the current state-of-the-art.

Key facts. Cited by 45 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Aug 2020.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 9; 2022: 13; 2023: 14; 2024: 4; 2025: 4; 2026: 1.

45 papers.

Sort:

By area:

  1. 2021Dynamic View Synthesis from Dynamic Monocular Videocited by 420
  2. 2023Robust Dynamic Radiance Fieldscited by 193
  3. 2023Consistent View Synthesis with Pose-Guided Diffusion Modelscited by 117
  4. 2021Geometry-Free View Synthesis: Transformers and no 3D Priorscited by 99
  5. 2022InfiniteNature-Zero: Learning Perpetual View Generation of Natural Scenes from Single Imagescited by 82
  6. 2023Consistent-1-to-3: Consistent Image to 3D View Synthesis via Geometry-aware Diffusion Modelscited by 79
  7. 2021Learning to Stylize Novel Viewscited by 76
  8. 2021360MonoDepth: High-Resolution 360deg Monocular Depth Estimationcited by 60
  9. 2022Single-View View Synthesis in the Wild with Learned Adaptive Multiplane Imagescited by 59
  10. 2021Learning Neural Light Fields with Ray-Space Embedding Networkscited by 49
  11. 2022CM-GAN: Image Inpainting with Cascaded Modulation GAN and Object-Aware Trainingcited by 49
  12. 2021SLIDE: Single Image 3D Photography with Soft Layering and Depth-aware Inpaintingcited by 48
33 more
  1. 20213D Photo Stylization: Learning to Generate Stylized Novel Views from a Single Imagecited by 45
  2. 2023Persistent Nature: A Generative Model of Unbounded 3D Worldscited by 44
  3. 2022IronDepth: Iterative Refinement of Single-View Depth using Surface Normal and its Uncertaintycited by 30
  4. 2023Fast View Synthesis of Casual Videos with Soup-of-Planescited by 22
  5. 2021Hybrid Neural Fusion for Full-frame Video Stabilizationcited by 21
  6. 20223D Moments from Near-Duplicate Photoscited by 15
  7. 2023Tiled Multiplane Images for Practical 3D Photographycited by 14
  8. 2022High-Resolution Depth Estimation for 360-degree Panoramas through Perspective and Panoramic Depth Images Registrationcited by 10
  9. 2023Clutter Detection and Removal in 3D Scenes with View-Consistent Inpaintingcited by 9
  10. 2022NeuralPassthrough: Learned Real-Time View Synthesis for VRcited by 8
  11. 2022Shakes on a Plane: Unsupervised Depth Estimation from Unstabilized Photographycited by 8
  12. 2023Learning 3D Photography Videos via Self-supervised Diffusion on Single Imagescited by 8
  13. 2024Finding Waldo: Towards Efficient Exploration of NeRF Scene Spacescited by 8
  14. 2021Endless Loops: Detecting and Animating Periodic Patterns in Still Imagescited by 7
  15. 2022A Practical Stereo Depth System for Smart Glassescited by 7
  16. 2023Single-Stage 3D Geometry-Preserving Depth Estimation Model Training on Dataset Mixtures with Uncalibrated Stereo Datacited by 6
  17. 2025Eye2Eye: A Simple Approach for Monocular-to-Stereo Video Synthesiscited by 6
  18. 2022Automated Distance Estimation for Wildlife Camera Trappingcited by 5
  19. 2022OmniSyn: Synthesizing 360 Videos with Wide-baseline Panoramascited by 5
  20. 2022Self-improving Multiplane-to-layer Images for Novel View Synthesiscited by 5
  21. 2022FloatingFusion: Depth from ToF and Image-stabilized Stereo Camerascited by 5
  22. 2024GeoGS3D: Single-view 3D Reconstruction via Geometric-aware Diffusion Model and Gaussian Splattingcited by 5
  23. 2023Single-View View Synthesis with Self-Rectified Pseudo-Stereocited by 4
  24. 2023VaLID: Variable-Length Input Diffusion for Novel View Synthesiscited by 4
  25. 2025Optimizing 4D Gaussians for Dynamic Scene Video from Single Landscape Imagescited by 4
  26. 2023ReShader: View-Dependent Highlights for Single Image View-Synthesiscited by 3
  27. 2023Painting 3D Nature in 2D: View Synthesis of Natural Scenes from a Single Semantic Maskcited by 2
  28. 2023Novel View Synthesis with View-Dependent Effects from a Single Imagecited by 2
  29. 2024PanoDreamer: Optimization-Based Single Image to 360 3D Scene With Diffusioncited by 2
  30. 2024Efficient Depth Estimation for Unstable Stereo Camera Systems on AR Glassescited by 1
  31. 2025CheapNVS: Real-Time On-Device Narrow-Baseline Novel View Synthesiscited by 1
  32. 2025SteROI-D: System Design and Mapping for Stereo Depth Inference on Regions of Interestcited by 0
  33. 2026Monocular Depth Estimation from a Single Image: Progress and Opportunitiescited by 0