mlsanityData to 14 Oct 2026

Multi-view 3D Models from Single Images with a Convolutional Network

arXiv 1511.06702 ↗First posted 20 Nov 2015cs.CVcited by 58

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Abstract (arXiv)

We present a convolutional network capable of inferring a 3D representation of a previously unseen object given a single image of this object. Concretely, the network can predict an RGB image and a depth map of the object as seen from an arbitrary view. Several of these depth maps fused together give a full point cloud of the object. The point cloud can in turn be transformed into a surface mesh. The network is trained on renderings of synthetic 3D models of cars and chairs. It successfully deals with objects on cluttered background and generates reasonable predictions for real images of cars.

Key facts. Cited by 58 papers in the map (data through 14 Oct 2026). First posted on arXiv 20 Nov 2015.

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Citing papers per year: 2021: 27; 2022: 12; 2023: 13; 2024: 5; 2025: 0; 2026: 1.

58 papers.

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  1. 2023DUSt3R: Geometric 3D Vision Made Easycited by 1,567
  2. 2021Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstructioncited by 652
  3. 2023Splatter Image: Ultra-Fast Single-View 3D Reconstructioncited by 364
  4. 2021Neural RGB-D Surface Reconstructioncited by 313
  5. 2021GRAM: Generative Radiance Manifolds for 3D-Aware Image Generationcited by 216
  6. 2022SparseFusion: Distilling View-conditioned Diffusion for 3D Reconstructioncited by 216
  7. 2021Neural Articulated Radiance Fieldcited by 196
  8. 2021Unconstrained Scene Generation with Locally Conditioned Radiance Fieldscited by 130
  9. 2023Consistent View Synthesis with Pose-Guided Diffusion Modelscited by 117
  10. 2021Geometry-Free View Synthesis: Transformers and no 3D Priorscited by 100
  11. 2021ShaRF: Shape-conditioned Radiance Fields from a Single Viewcited by 92
  12. 2024LN3DIFF++: Scalable Latent Neural Fields Diffusion for Speedy 3D Generationcited by 92
38 more
  1. 2021PixelSynth: Generating a 3D-Consistent Experience from a Single Imagecited by 82
  2. 2022Pix2NeRF: Unsupervised Conditional π-GAN for Single Image to Neural Radiance Fields Translationcited by 73
  3. 2022GRAM-HD: 3D-Consistent Image Generation at High Resolution with Generative Radiance Manifoldscited by 73
  4. 2023Free3D: Consistent Novel View Synthesis without 3D Representationcited by 72
  5. 2023Suspicion-Agent: Playing Imperfect Information Games with Theory of Mind Aware GPT-4cited by 68
  6. 2022High-fidelity 3D GAN Inversion by Pseudo-multi-view Optimizationcited by 65
  7. 2024Advances in 3D Generation: A Surveycited by 63
  8. 2022FWD: Real-time Novel View Synthesis with Forward Warping and Depthcited by 39
  9. 2021SAIL-VOS 3D: A Synthetic Dataset and Baselines for Object Detection and 3D Mesh Reconstruction from Video Datacited by 38
  10. 2023Make Encoder Great Again in 3D GAN Inversion through Geometry and Occlusion-Aware Encodingcited by 35
  11. 2021Video Autoencoder: self-supervised disentanglement of static 3D structure and motioncited by 34
  12. 2023DreamSparse: Escaping from Plato's Cave with 2D Frozen Diffusion Model Given Sparse Viewscited by 31
  13. 2021Cascaded Cross MLP-Mixer GANs for Cross-View Image Translationcited by 21
  14. 2022Pixel2Mesh++: 3D Mesh Generation and Refinement from Multi-View Imagescited by 21
  15. 2021Cross-View Exocentric to Egocentric Video Synthesiscited by 20
  16. 2021Moving in a 360 World: Synthesizing Panoramic Parallaxes from a Single Panoramacited by 19
  17. 2021Augmenting Implicit Neural Shape Representations with Explicit Deformation Fieldscited by 19
  18. 2024TryOffDiff: Virtual-Try-Off via High-Fidelity Garment Reconstruction using Diffusion Modelscited by 19
  19. 2021Recognizing Actions in Videos from Unseen Viewpointscited by 18
  20. 2023SNeRL: Semantic-aware Neural Radiance Fields for Reinforcement Learningcited by 16
  21. 2022SymmNeRF: Learning to Explore Symmetry Prior for Single-View View Synthesiscited by 13
  22. 2022Bridging Implicit and Explicit Geometric Transformation for Single-Image View Synthesiscited by 11
  23. 2023Where and How: Mitigating Confusion in Neural Radiance Fields from Sparse Inputscited by 11
  24. 2021Deep View Synthesis via Self-Consistent Generative Networkcited by 10
  25. 2021Unsupervised Novel View Synthesis from a Single Imagecited by 8
  26. 2022Local and Global GANs with Semantic-Aware Upsampling for Image Generationcited by 8
  27. 2022Generative Deformable Radiance Fields for Disentangled Image Synthesis of Topology-Varying Objectscited by 8
  28. 2023Neural Radiance Fields: Past, Present, and Futurecited by 8
  29. 2023Viewpoint Textual Inversion: Discovering Scene Representations and 3D View Control in 2D Diffusion Modelscited by 7
  30. 2022Point Cloud Scene Completion with Joint Color and Semantic Estimation from Single RGB-D Imagecited by 6
  31. 2024Query-based Semantic Gaussian Field for Scene Representation in Reinforcement Learningcited by 6
  32. 2021Novel View Synthesis via Depth-guided Skip Connectionscited by 5
  33. 2021Multi-Category Mesh Reconstruction From Image Collectionscited by 5
  34. 2022PVSeRF: Joint Pixel-, Voxel- and Surface-Aligned Radiance Field for Single-Image Novel View Synthesiscited by 5
  35. 2021Learning Neural Representation of Camera Pose with Matrix Representation of Pose Shift via View Synthesiscited by 4
  36. 2023Single-View View Synthesis with Self-Rectified Pseudo-Stereocited by 4
  37. 2021Aug3D-RPN: Improving Monocular 3D Object Detection by Synthetic Images with Virtual Depthcited by 3
  38. 2021STR-GQN: Scene Representation and Rendering for Unknown Cameras Based on Spatial Transformation Routingcited by 2

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