CompNVS: Novel View Synthesis with Scene Completion
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Abstract (arXiv)
We introduce a scalable framework for novel view synthesis from RGB-D images with largely incomplete scene coverage. While generative neural approaches have demonstrated spectacular results on 2D images, they have not yet achieved similar photorealistic results in combination with scene completion where a spatial 3D scene understanding is essential. To this end, we propose a generative pipeline performing on a sparse grid-based neural scene representation to complete unobserved scene parts via a learned distribution of scenes in a 2.5D-3D-2.5D manner. We process encoded image features in 3D space with a geometry completion network and a subsequent texture inpainting network to extrapolate the missing area. Photorealistic image sequences can be finally obtained via consistency-relevant differentiable rendering. Comprehensive experiments show that the graphical outputs of our method outperform the state of the art, especially within unobserved scene parts.
Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 27 of its 30 references that are in the map. First posted on arXiv 23 Jul 2022.
Builds on
27 of 30 references.
References · 27
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15 more
- 2020GRAF: Generative Radiance Fields for 3D-Aware Image Synthesiscited by 689
- 2018Free-Form Image Inpainting with Gated Convolutioncited by 594
- 2018Generative Image Inpainting with Contextual Attentioncited by 580
- 2021Habitat 2.0: Training Home Assistants to Rearrange their Habitatcited by 511
- 2021ARKitScenes: A Diverse Real-World Dataset For 3D Indoor Scene Understanding Using Mobile RGB-D Datacited by 454
- 2019SynSin: End-to-end View Synthesis from a Single Imagecited by 364
- 2017Toward Multimodal Image-to-Image Translationcited by 296
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- 2020World-Consistent Video-to-Video Synthesiscited by 69
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Built on by
Citing papers per year: 2022: 3; 2023: 3; 2024: 1; 2025: 2.
9 papers.
- 2022Removing Objects From Neural Radiance Fieldscited by 66
- 2023Watch Your Steps: Local Image and Scene Editing by Text Instructionscited by 50
- 2023Reference-guided Controllable Inpainting of Neural Radiance Fieldscited by 40
- 2024Sat2Scene: 3D Urban Scene Generation from Satellite Images with Diffusioncited by 27
- 2025WorldGen: From Text to Traversable and Interactive 3D Worldscited by 19
- 2022SPARF: Large-Scale Learning of 3D Sparse Radiance Fields from Few Input Imagescited by 17
- 2022Free-form 3D Scene Inpainting with Dual-stream GANcited by 6
- 2023SparseGNV: Generating Novel Views of Indoor Scenes with Sparse Input Viewscited by 2
- 2025Beyond Darkness: Thermal-Supervised 3D Gaussian Splatting for Low-Light Novel View Synthesiscited by 1
- 2025WorldGen: From Text to Traversable and Interactive 3D Worlds20 Nov 2025
- 2025Beyond Darkness: Thermal-Supervised 3D Gaussian Splatting for Low-Light Novel View Synthesis17 Nov 2025
- 2024Sat2Scene: 3D Urban Scene Generation from Satellite Images with Diffusion19 Jan 2024
- 2023Watch Your Steps: Local Image and Scene Editing by Text Instructions17 Aug 2023
- 2023SparseGNV: Generating Novel Views of Indoor Scenes with Sparse Input Views11 May 2023
- 2023Reference-guided Controllable Inpainting of Neural Radiance Fields19 Apr 2023
- 2022Removing Objects From Neural Radiance Fields22 Dec 2022
- 2022SPARF: Large-Scale Learning of 3D Sparse Radiance Fields from Few Input Images18 Dec 2022
- 2022Free-form 3D Scene Inpainting with Dual-stream GAN16 Dec 2022