NOVA: NOvel View Augmentation for Neural Composition of Dynamic Objects
Not on the map. Why?
Abstract (arXiv)
We propose a novel-view augmentation (NOVA) strategy to train NeRFs for photo-realistic 3D composition of dynamic objects in a static scene. Compared to prior work, our framework significantly reduces blending artifacts when inserting multiple dynamic objects into a 3D scene at novel views and times; achieves comparable PSNR without the need for additional ground truth modalities like optical flow; and overall provides ease, flexibility, and scalability in neural composition. Our codebase is on GitHub.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 20 of its 24 references that are in the map. First posted on arXiv 24 Aug 2023.
Builds on
20 of 24 references.
References · 20
- 2020D-NeRF: Neural Radiance Fields for Dynamic Scenescited by 1,465
- 2020Nerfies: Deformable Neural Radiance Fieldscited by 1,198
- 2020GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fieldscited by 785
- 2020Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenescited by 751
- 2022Block-NeRF: Scalable Large Scene Neural View Synthesiscited by 724
- 2020Non-Rigid Neural Radiance Fields: Reconstruction and Novel View Synthesis of a Dynamic Scene From Monocular Videocited by 471
- 2021Dynamic View Synthesis from Dynamic Monocular Videocited by 420
- 2020Space-time Neural Irradiance Fields for Free-Viewpoint Videocited by 414
- 2020Neural Scene Graphs for Dynamic Scenescited by 298
- 2020Neural Radiance Flow for 4D View Synthesis and Video Processingcited by 270
- 2021Learning Object-Compositional Neural Radiance Field for Editable Scene Renderingcited by 228
- 2019Inverse Rendering for Complex Indoor Scenes: Shape, Spatially-Varying Lighting and SVBRDF from a Single Imagecited by 203
8 more
- 2020Novel View Synthesis of Dynamic Scenes with Globally Coherent Depths from a Monocular Cameracited by 166
- 2021DriveGAN: Towards a Controllable High-Quality Neural Simulationcited by 125
- 2019Neural Inverse Rendering of an Indoor Scene from a Single Imagecited by 101
- 2020Object-Centric Neural Scene Renderingcited by 90
- 2019Deep Sky Modeling for Single Image Outdoor Lighting Estimationcited by 66
- 2022MonoNeRF: Learning a Generalizable Dynamic Radiance Field from Monocular Videoscited by 63
- 2022IRISformer: Dense Vision Transformers for Single-Image Inverse Rendering in Indoor Scenescited by 62
- 2022Neural Light Field Estimation for Street Scenes with Differentiable Virtual Object Insertioncited by 35
Built on by
Citing papers per year: 2025: 1.
1 paper.