mlsanityData to 7 Oct 2026

NeuralHumanFVV: Real-Time Neural Volumetric Human Performance Rendering using RGB Cameras

arXiv 2103.07700 ↗First posted 13 Mar 2021cs.CVcited by 40

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Abstract (arXiv)

4D reconstruction and rendering of human activities is critical for immersive VR/AR experience.Recent advances still fail to recover fine geometry and texture results with the level of detail present in the input images from sparse multi-view RGB cameras. In this paper, we propose NeuralHumanFVV, a real-time neural human performance capture and rendering system to generate both high-quality geometry and photo-realistic texture of human activities in arbitrary novel views. We propose a neural geometry generation scheme with a hierarchical sampling strategy for real-time implicit geometry inference, as well as a novel neural blending scheme to generate high resolution (e.g., 1k) and photo-realistic texture results in the novel views. Furthermore, we adopt neural normal blending to enhance geometry details and formulate our neural geometry and texture rendering into a multi-task learning framework. Extensive experiments demonstrate the effectiveness of our approach to achieve high-quality geometry and photo-realistic free view-point reconstruction for challenging human performances.

Key facts. Cited by 40 papers in the map (data through 7 Oct 2026). Builds on 33 of its 75 references that are in the map. First posted on arXiv 13 Mar 2021.

Builds on

33 of 75 references.

References · 33

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  2. 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,682
  3. 2018Occupancy Networks: Learning 3D Reconstruction in Function Spacecited by 2,037
  4. 2019Expressive Body Capture: 3D Hands, Face, and Body from a Single Imagecited by 1,600
  5. 2016Realtime Multi-Person 2D Pose Estimation using Part Affinity Fieldscited by 1,061
  6. 2020Neural Sparse Voxel Fieldscited by 959
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  9. 2019PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitizationcited by 818
  10. 2018DensePose: Dense Human Pose Estimation In The Wildcited by 573
  11. 2020PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitizationcited by 521
  12. 2018DeepVoxels: Learning Persistent 3D Feature Embeddingscited by 401
21 more
  1. 2019Neural Point-Based Graphicscited by 326
  2. 2020State of the Art on Neural Renderingcited by 276
  3. 2019Multi-Garment Net: Learning to Dress 3D People from Imagescited by 244
  4. 2018Total Capture: A 3D Deformation Model for Tracking Faces, Hands, and Bodiescited by 239
  5. 2020Free View Synthesiscited by 231
  6. 2019DeepHuman: 3D Human Reconstruction from a Single Imagecited by 182
  7. 2019Tex2Shape: Detailed Full Human Body Geometry From a Single Imagecited by 166
  8. 2018Monocular Total Capture: Posing Face, Body, and Hands in the Wildcited by 162
  9. 2017VNect: Real-time 3D Human Pose Estimation with a Single RGB Cameracited by 129
  10. 2019Neural Rerendering in the Wildcited by 121
  11. 2018DoubleFusion: Real-time Capture of Human Performances with Inner Body Shapes from a Single Depth Sensorcited by 95
  12. 2018LiveCap: Real-time Human Performance Capture from Monocular Videocited by 93
  13. 2019360-Degree Textures of People in Clothing from a Single Imagecited by 75
  14. 2020Monocular Real-Time Volumetric Performance Capturecited by 74
  15. 2019EventCap: Monocular 3D Capture of High-Speed Human Motions using an Event Cameracited by 65
  16. 2017MonoPerfCap: Human Performance Capture from Monocular Videocited by 63
  17. 20193DPeople: Modeling the Geometry of Dressed Humanscited by 58
  18. 2021ChallenCap: Monocular 3D Capture of Challenging Human Performances using Multi-Modal Referencescited by 26
  19. 2016FlyCap: Markerless Motion Capture Using Multiple Autonomous Flying Camerascited by 23
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  21. 2019Volumetric Capture of Humans with a Single RGBD Camera via Semi-Parametric Learningcited by 13

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 9; 2022: 10; 2023: 10; 2024: 5; 2025: 5; 2026: 1.

40 papers.

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  1. 2021Neural Fields in Visual Computing and Beyondcited by 539
  2. 2021Editable Free-viewpoint Video Using a Layered Neural Representationcited by 148
  3. 2021HumanNeRF: Efficiently Generated Human Radiance Field from Sparse Inputscited by 112
  4. 2023Diffusion-Guided Reconstruction of Everyday Hand-Object Interaction Clipscited by 73
  5. 2023HiFi4G: High-Fidelity Human Performance Rendering via Compact Gaussian Splattingcited by 68
  6. 2022NeuralDome: A Neural Modeling Pipeline on Multi-View Human-Object Interactionscited by 67
  7. 2022Human Performance Modeling and Rendering via Neural Animated Meshcited by 64
  8. 2021DoubleField: Bridging the Neural Surface and Radiance Fields for High-fidelity Human Reconstruction and Renderingcited by 52
  9. 2023Representing Volumetric Videos as Dynamic MLP Mapscited by 51
  10. 2022NeuralHOFusion: Neural Volumetric Rendering under Human-object Interactionscited by 44
  11. 2022Relighting4D: Neural Relightable Human from Videoscited by 41
  12. 2021SportsCap: Monocular 3D Human Motion Capture and Fine-grained Understanding in Challenging Sports Videoscited by 40
28 more
  1. 2021Neural Free-Viewpoint Performance Rendering under Complex Human-object Interactionscited by 37
  2. 2024A Survey of Camouflaged Object Detection and Beyondcited by 37
  3. 2022Animatable Implicit Neural Representations for Creating Realistic Avatars from Videoscited by 33
  4. 2022HumanGen: Generating Human Radiance Fields with Explicit Priorscited by 33
  5. 2023HOSNeRF: Dynamic Human-Object-Scene Neural Radiance Fields from a Single Videocited by 33
  6. 2024Robust Dual Gaussian Splatting for Immersive Human-centric Volumetric Videoscited by 30
  7. 2022AvatarCap: Animatable Avatar Conditioned Monocular Human Volumetric Capturecited by 25
  8. 2023Instant-NVR: Instant Neural Volumetric Rendering for Human-object Interactions from Monocular RGBD Streamcited by 23
  9. 2023Drivable Avatar Clothing: Faithful Full-Body Telepresence with Dynamic Clothing Driven by Sparse RGB-D Inputcited by 22
  10. 2023TeTriRF: Temporal Tri-Plane Radiance Fields for Efficient Free-Viewpoint Videocited by 22
  11. 2024GPS-Gaussian+: Generalizable Pixel-wise 3D Gaussian Splatting for Real-Time Human-Scene Rendering from Sparse Viewscited by 22
  12. 2021iButter: Neural Interactive Bullet Time Generator for Human Free-viewpoint Renderingcited by 16
  13. 2024A Survey on 3D Human Avatar Modeling -- From Reconstruction to Generationcited by 13
  14. 2022NeuVV: Neural Volumetric Videos with Immersive Rendering and Editingcited by 12
  15. 2023Learning Visibility Field for Detailed 3D Human Reconstruction and Relightingcited by 11
  16. 2024Tele-Aloha: A Low-budget and High-authenticity Telepresence System Using Sparse RGB Camerascited by 11
  17. 2021Few-shot Neural Human Performance Rendering from Sparse RGBD Videoscited by 8
  18. 2022HDhuman: High-quality Human Novel-view Rendering from Sparse Viewscited by 8
  19. 2025RePerformer: Immersive Human-centric Volumetric Videos from Playback to Photoreal Reperformancecited by 8
  20. 2022WarpingGAN: Warping Multiple Uniform Priors for Adversarial 3D Point Cloud Generationcited by 7
  21. 2023MVHuman: Tailoring 2D Diffusion with Multi-view Sampling For Realistic 3D Human Generationcited by 6
  22. 2025EvolvingGS: High-Fidelity Streamable Volumetric Video via Evolving 3D Gaussian Representationcited by 3
  23. 2023NeVRF: Neural Video-based Radiance Fields for Long-duration Sequencescited by 1
  24. 2025Tessellation GS: Neural Mesh Gaussians for Robust Monocular Reconstruction of Dynamic Objectscited by 1
  25. 2021LookinGoodπ: Real-time Person-independent Neural Re-rendering for High-quality Human Performance Capturecited by 0
  26. 2025Uncertainty Aware Human-machine Collaboration in Camouflaged Object Detectioncited by 0
  27. 2025Physically Plausible Human-Object Rendering from Sparse Views via 3D Gaussian Splattingcited by 0
  28. 2026Director: Instance-aware Gaussian Splatting for Dynamic Scene Modeling and Understandingcited by 0