mlsanityData to 14 Oct 2026

Template-free Articulated Neural Point Clouds for Reposable View Synthesis

arXiv 2305.19065 ↗First posted 30 May 2023cs.CV cs.GRcited by 15

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Abstract (arXiv)

Dynamic Neural Radiance Fields (NeRFs) achieve remarkable visual quality when synthesizing novel views of time-evolving 3D scenes. However, the common reliance on backward deformation fields makes reanimation of the captured object poses challenging. Moreover, the state of the art dynamic models are often limited by low visual fidelity, long reconstruction time or specificity to narrow application domains. In this paper, we present a novel method utilizing a point-based representation and Linear Blend Skinning (LBS) to jointly learn a Dynamic NeRF and an associated skeletal model from even sparse multi-view video. Our forward-warping approach achieves state-of-the-art visual fidelity when synthesizing novel views and poses while significantly reducing the necessary learning time when compared to existing work. We demonstrate the versatility of our representation on a variety of articulated objects from common datasets and obtain reposable 3D reconstructions without the need of object-specific skeletal templates. Code will be made available at https://github.com/lukasuz/Articulated-Point-NeRF.

Key facts. Cited by 15 papers in the map (data through 14 Oct 2026). Builds on 100 of its 122 references that are in the map. First posted on arXiv 30 May 2023.

Builds on

100 of 122 references.

References · 100

  1. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,177
  2. 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,723
  3. 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,689
  4. 2020Implicit Neural Representations with Periodic Activation Functionscited by 2,238
  5. 2020Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domainscited by 2,200
  6. 2018Occupancy Networks: Learning 3D Reconstruction in Function Spacecited by 2,041
  7. 2021Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fieldscited by 2,032
  8. 2019Expressive Body Capture: 3D Hands, Face, and Body from a Single Imagecited by 1,612
  9. 2020D-NeRF: Neural Radiance Fields for Dynamic Scenescited by 1,465
  10. 2022TensoRF: Tensorial Radiance Fieldscited by 1,280
  11. 2020NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collectionscited by 1,232
  12. 2020Nerfies: Deformable Neural Radiance Fieldscited by 1,198
38 more
  1. 2018Learning Implicit Fields for Generative Shape Modelingcited by 1,060
  2. 2021Direct Voxel Grid Optimization: Super-fast Convergence for Radiance Fields Reconstructioncited by 964
  3. 2020Neural Sparse Voxel Fieldscited by 959
  4. 2021PlenOctrees for Real-time Rendering of Neural Radiance Fieldscited by 905
  5. 2017End-to-end Recovery of Human Shape and Posecited by 885
  6. 2019Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representationscited by 864
  7. 2020NeRF++: Analyzing and Improving Neural Radiance Fieldscited by 861
  8. 2019PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitizationcited by 818
  9. 2020Convolutional Occupancy Networkscited by 761
  10. 2020Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenescited by 751
  11. 2023K-Planes: Explicit Radiance Fields in Space, Time, and Appearancecited by 746
  12. 2022Block-NeRF: Scalable Large Scene Neural View Synthesiscited by 724
  13. 2020Implicit Geometric Regularization for Learning Shapescited by 710
  14. 2019Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervisioncited by 700
  15. 2021KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPscited by 673
  16. 2021UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstructioncited by 646
  17. 2020Neural Body: Implicit Neural Representations with Structured Latent Codes for Novel View Synthesis of Dynamic Humanscited by 634
  18. 2019Learning to Reconstruct 3D Human Pose and Shape via Model-fitting in the Loopcited by 627
  19. 2019VIBE: Video Inference for Human Body Pose and Shape Estimationcited by 620
  20. 2023HexPlane: A Fast Representation for Dynamic Scenescited by 587
  21. 2020PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitizationcited by 521
  22. 2021FastNeRF: High-Fidelity Neural Rendering at 200FPScited by 511
  23. 2022Point-NeRF: Point-based Neural Radiance Fieldscited by 503
  24. 2020NeRV: Neural Reflectance and Visibility Fields for Relighting and View Synthesiscited by 496
  25. 2022HumanNeRF: Free-viewpoint Rendering of Moving People from Monocular Videocited by 483
  26. 2020Non-Rigid Neural Radiance Fields: Reconstruction and Novel View Synthesis of a Dynamic Scene From Monocular Videocited by 471
  27. 2021Baking Neural Radiance Fields for Real-Time View Synthesiscited by 468
  28. 2020Dynamic Neural Radiance Fields for Monocular 4D Facial Avatar Reconstructioncited by 467
  29. 2021Neural Geometric Level of Detail: Real-time Rendering with Implicit 3D Shapescited by 426
  30. 2021Dynamic View Synthesis from Dynamic Monocular Videocited by 420
  31. 2020Space-time Neural Irradiance Fields for Free-Viewpoint Videocited by 414
  32. 2018DeepVoxels: Learning Persistent 3D Feature Embeddingscited by 405
  33. 2019SAL: Sign Agnostic Learning of Shapes from Raw Datacited by 390
  34. 2020Local Implicit Grid Representations for 3D Scenescited by 373
  35. 2021Advances in Neural Renderingcited by 365
  36. 2021Animatable Neural Radiance Fields for Modeling Dynamic Human Bodiescited by 361
  37. 2022Fast Dynamic Radiance Fields with Time-Aware Neural Voxelscited by 346
  38. 2021AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesiscited by 339

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 2; 2024: 3; 2025: 5; 2026: 5.

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  1. 2023Neural Parametric Gaussians for Monocular Non-Rigid Object Reconstructioncited by 61
  2. 2024Recent Trends in 3D Reconstruction of General Non-Rigid Scenescited by 28
  3. 2025Infinite Mobility: Scalable High-Fidelity Synthesis of Articulated Objects via Procedural Generationcited by 19
  4. 2025RigGS: Rigging of 3D Gaussians for Modeling Articulated Objects in Videoscited by 14
  5. 2024Template-free Articulated Gaussian Splatting for Real-time Reposable Dynamic View Synthesiscited by 13
  6. 2025RePerformer: Immersive Human-centric Volumetric Videos from Playback to Photoreal Reperformancecited by 8
  7. 2023Dynamic Appearance Particle Neural Radiance Fieldcited by 6
  8. 2025Surface-Aware Distilled 3D Semantic Featurescited by 5
  9. 2026SV-GS: Sparse View 4D Reconstruction with Skeleton-Driven Gaussian Splattingcited by 1
  10. 2026MorphGS: Morphology-Adaptive Articulated 3D Motion Transfer from Videoscited by 1
  11. 2024MotionDreamer: Exploring Semantic Video Diffusion features for Zero-Shot 3D Mesh Animationcited by 0
  12. 2025Learning High-Fidelity Robot Self-Model with Articulated 3D Gaussian Splattingcited by 0
3 more
  1. 2026GaussiAnimate: Rig Animatable Categories with Level of Dynamicscited by 0
  2. 2026RigPAPR: Rig-Based Animation of Static Neural Point Clouds from a Fixed-Viewpoint Videocited by 0
  3. 2026G-Skin: Learning to Bind 3D Gaussians with Generative Visual Priorscited by 0