mlsanityData to 14 Oct 2026

PARF: Primitive-Aware Radiance Fusion for Indoor Scene Novel View Synthesis

arXiv 2309.17190 ↗First posted 29 Sep 2023cs.CV cs.AIcited by 5

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Abstract (arXiv)

This paper proposes a method for fast scene radiance field reconstruction with strong novel view synthesis performance and convenient scene editing functionality. The key idea is to fully utilize semantic parsing and primitive extraction for constraining and accelerating the radiance field reconstruction process. To fulfill this goal, a primitive-aware hybrid rendering strategy was proposed to enjoy the best of both volumetric and primitive rendering. We further contribute a reconstruction pipeline conducts primitive parsing and radiance field learning iteratively for each input frame which successfully fuses semantic, primitive, and radiance information into a single framework. Extensive evaluations demonstrate the fast reconstruction ability, high rendering quality, and convenient editing functionality of our method.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 28 of its 44 references that are in the map. First posted on arXiv 29 Sep 2023.

Builds on

28 of 44 references.

References · 28

  1. 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,723
  2. 2017ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenescited by 3,117
  3. 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,689
  4. 2021Plenoxels: Radiance Fields without Neural Networkscited by 1,613
  5. 2020NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collectionscited by 1,232
  6. 2015ORB-SLAM: a Versatile and Accurate Monocular SLAM Systemcited by 988
  7. 2021Direct Voxel Grid Optimization: Super-fast Convergence for Radiance Fields Reconstructioncited by 964
  8. 2020Neural Sparse Voxel Fieldscited by 959
  9. 2019The Replica Dataset: A Digital Replica of Indoor Spacescited by 904
  10. 2020NeRF++: Analyzing and Improving Neural Radiance Fieldscited by 861
  11. 2018MVSNet: Depth Inference for Unstructured Multi-view Stereocited by 788
  12. 2021Depth-supervised NeRF: Fewer Views and Faster Training for Freecited by 735
16 more
  1. 2021IBRNet: Learning Multi-View Image-Based Renderingcited by 703
  2. 2021RegNeRF: Regularizing Neural Radiance Fields for View Synthesis from Sparse Inputscited by 615
  3. 2021NICE-SLAM: Neural Implicit Scalable Encoding for SLAMcited by 589
  4. 2022MonoSDF: Exploring Monocular Geometric Cues for Neural Implicit Surface Reconstructioncited by 470
  5. 2021In-Place Scene Labelling and Understanding with Implicit Scene Representationcited by 415
  6. 20163DMatch: Learning Local Geometric Descriptors from RGB-D Reconstructionscited by 336
  7. 2021Neural RGB-D Surface Reconstructioncited by 313
  8. 2022MobileNeRF: Exploiting the Polygon Rasterization Pipeline for Efficient Neural Field Rendering on Mobile Architecturescited by 311
  9. 2021NeuralRecon: Real-Time Coherent 3D Reconstruction from Monocular Videocited by 241
  10. 2022NeRF-SLAM: Real-Time Dense Monocular SLAM with Neural Radiance Fieldscited by 188
  11. 2021InfoNeRF: Ray Entropy Minimization for Few-Shot Neural Volume Renderingcited by 182
  12. 2022Neural 3D Scene Reconstruction with the Manhattan-world Assumptioncited by 123
  13. 2022NeRFusion: Fusing Radiance Fields for Large-Scale Scene Reconstructioncited by 100
  14. 2022PlanarRecon: Real-time 3D Plane Detection and Reconstruction from Posed Monocular Videoscited by 27
  15. 2022NeurMiPs: Neural Mixture of Planar Experts for View Synthesiscited by 23
  16. 2018Fast Cylinder and Plane Extraction from Depth Cameras for Visual Odometrycited by 6

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Cited by year

Citing papers per year: 2023: 2; 2024: 1; 2025: 2.

5 papers.