wildNeRF: Complete view synthesis of in-the-wild dynamic scenes captured using sparse monocular data
Not on the map. Why?
Abstract (arXiv)
We present a novel neural radiance model that is trainable in a self-supervised manner for novel-view synthesis of dynamic unstructured scenes. Our end-to-end trainable algorithm learns highly complex, real-world static scenes within seconds and dynamic scenes with both rigid and non-rigid motion within minutes. By differentiating between static and motion-centric pixels, we create high-quality representations from a sparse set of images. We perform extensive qualitative and quantitative evaluation on existing benchmarks and set the state-of-the-art on performance measures on the challenging NVIDIA Dynamic Scenes Dataset. Additionally, we evaluate our model performance on challenging real-world datasets such as Cholec80 and SurgicalActions160.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 35 of its 58 references that are in the map. First posted on arXiv 20 Sep 2022.
Builds on
35 of 58 references.
References · 35
- 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,029
- 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,698
- 2020RAFT: Recurrent All-Pairs Field Transforms for Optical Flowcited by 2,385
- 2021Plenoxels: Radiance Fields without Neural Networkscited by 1,607
- 2019Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfercited by 1,484
- 2020D-NeRF: Neural Radiance Fields for Dynamic Scenescited by 1,459
- 2017VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detectioncited by 1,323
- 2022TensoRF: Tensorial Radiance Fieldscited by 1,275
- 2020NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collectionscited by 1,230
- 2020Nerfies: Deformable Neural Radiance Fieldscited by 1,194
- 2020Neural Sparse Voxel Fieldscited by 959
- 2021PlenOctrees for Real-time Rendering of Neural Radiance Fieldscited by 904
23 more
- 2020Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenescited by 750
- 2021Depth-supervised NeRF: Fewer Views and Faster Training for Freecited by 732
- 2021KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPscited by 672
- 2018PointConv: Deep Convolutional Networks on 3D Point Cloudscited by 656
- 2021BARF: Bundle-Adjusting Neural Radiance Fieldscited by 641
- 2019Deep Learning for 3D Point Clouds: A Surveycited by 557
- 2020Tracking Objects as Pointscited by 483
- 2020Non-Rigid Neural Radiance Fields: Reconstruction and Novel View Synthesis of a Dynamic Scene From Monocular Videocited by 470
- 20193D Packing for Self-Supervised Monocular Depth Estimationcited by 437
- 2021Dynamic View Synthesis from Dynamic Monocular Videocited by 420
- 2016EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videoscited by 366
- 2021NeRF in the Dark: High Dynamic Range View Synthesis from Noisy Raw Imagescited by 336
- 2021Dense Depth Priors for Neural Radiance Fields from Sparse Input Viewscited by 301
- 2021GeoNeRF: Generalizing NeRF with Geometry Priorscited by 195
- 2021NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereocited by 191
- 2017SEGCloud: Semantic Segmentation of 3D Point Cloudscited by 178
- 2020Novel View Synthesis of Dynamic Scenes with Globally Coherent Depths from a Monocular Cameracited by 166
- 2022VoxGRAF: Fast 3D-Aware Image Synthesis with Sparse Voxel Gridscited by 133
- 2021T"oRF: Time-of-Flight Radiance Fields for Dynamic Scene View Synthesiscited by 88
- 2019Deep Optics for Monocular Depth Estimation and 3D Object Detectioncited by 65
- 2021FiG-NeRF: Figure-Ground Neural Radiance Fields for 3D Object Category Modellingcited by 47
- 2018Pixels, voxels, and views: A study of shape representations for single view 3D object shape predictioncited by 27
- 2021Template NeRF: Towards Modeling Dense Shape Correspondences from Category-Specific Object Imagescited by 5
Built on by
Citing papers per year: 2023: 3.
3 papers.
- 2023WaveNeRF: Wavelet-based Generalizable Neural Radiance Fieldscited by 24
- 2023RefiNeRF: Modelling dynamic neural radiance fields with inconsistent or missing camera parameterscited by 2
- 2023SurGNN: Explainable visual scene understanding and assessment of surgical skill using graph neural networkscited by 0
- 2023SurGNN: Explainable visual scene understanding and assessment of surgical skill using graph neural networks24 Aug 2023
- 2023WaveNeRF: Wavelet-based Generalizable Neural Radiance Fields9 Aug 2023
- 2023RefiNeRF: Modelling dynamic neural radiance fields with inconsistent or missing camera parameters15 Mar 2023