awesome-NeRF
A curated list of awesome neural radiance fields (NeRF) papers.
https://github.com/MatrixBrain/awesome-NeRF
Last synced: 6 days ago
JSON representation
-
Papers
-
NeRF Related Tasks
- Torch - View Reconstruction](https://openaccess.thecvf.com/content/ICCV2021/papers/Oechsle_UNISURF_Unifying_Neural_Implicit_Surfaces_and_Radiance_Fields_for_Multi-View_ICCV_2021_paper.pdf)|
- Geometry-Guided Progressive NeRF for Generalizable and Efficient Neural Human Rendering
- Torch - time and Accurate Neural Radiance Fields with Deterministic Integration for Volume Rendering](https://openaccess.thecvf.com/content/CVPR2022/papers/Wu_DIVeR_Real-Time_and_Accurate_Neural_Radiance_Fields_With_Deterministic_Integration_CVPR_2022_paper.pdf)|
- Urban Radiance Fields
- Geometry-Guided Progressive NeRF for Generalizable and Efficient Neural Human Rendering
- Reinforcement Learning with Neural Radiance Fields - rl/)|
- Factorized and Controllable Neural Re-Rendering of Outdoor Scene for Photo Extrapolation
- Torch - NeRF: Neural Inverse Rendering for Multi-view Photometric Stereo](https://ywq.github.io/psnerf/)|[Project Page](https://ywq.github.io/psnerf/)|
- Torch - based Implicit Field for Geometry and Texture Editing](https://arxiv.org/pdf/2207.11911.pdf)|[Project Page](https://zju3dv.github.io/neumesh/)|
- Jittor - Editing: Geometry Editing of Neural Radiance Fields](https://openaccess.thecvf.com/content/CVPR2022/papers/Yuan_NeRF-Editing_Geometry_Editing_of_Neural_Radiance_Fields_CVPR_2022_paper.pdf)|
- Torch
- RigNeRF: Fully Controllable Neural 3D Portraits
- CoNeRF: Controllable Neural Radiance Fields
- Torch - Compositional Neural Radiance Field for Editable Scene Rendering](https://openaccess.thecvf.com/content/ICCV2021/papers/Yang_Learning_Object-Compositional_Neural_Radiance_Field_for_Editable_Scene_Rendering_ICCV_2021_paper.pdf)|[Project Page](https://zju3dv.github.io/object_nerf/)|
- Torch
- Torch - niemeyer.github.io/project-pages/giraffe/index.html)|
- Torch
- Torch - Paper.pdf)|[Project Page](https://www.guandaoyang.com/NFGP/)|
- Generative Neural Articulated Radiance Fields
- Torch - GAN into StyleGAN for Editable Portrait Image Synthesis](https://arxiv.org/pdf/2207.10257.pdf)||
- Torch - View Semantic Masks to Neural Radiance Fields](https://arxiv.org/pdf/2203.10821.pdf)|[Project Page](https://donydchen.github.io/sem2nerf/)|
- LOLNeRF: Learn from One Look - vision.github.io/lolnerf/)|
- Torch - time NeRF-based Parametric Head Model](https://openaccess.thecvf.com/content/CVPR2022/papers/Hong_HeadNeRF_A_Real-Time_NeRF-Based_Parametric_Head_Model_CVPR_2022_paper.pdf)|
- Torch - GAN for Single Image to NeuralRadiance Fields Translation](https://openaccess.thecvf.com/content/CVPR2022/papers/Cai_Pix2NeRF_Unsupervised_Conditional_p-GAN_for_Single_Image_to_Neural_Radiance_CVPR_2022_paper.pdf)|
- Torch - NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis](https://openaccess.thecvf.com/content/ICCV2021/papers/Guo_AD-NeRF_Audio_Driven_Neural_Radiance_Fields_for_Talking_Head_Synthesis_ICCV_2021_paper.pdf)|
- Dynamic Neural Radiance Fields for Monocular 4D Facial Avatar Reconstruction - Facial-Avatars/)|
- Comming Soon - Plenoxels: Self-Calibrating High Dynamic Range Radiance Fields](https://arxiv.org/pdf/2208.06787.pdf)||
- Torch - Shot Talking Head Synthesis](https://arxiv.org/pdf/2207.11770.pdf)|[Project Page](https://sstzal.github.io/DFRF/)|
- Torch - GAN into StyleGAN for Editable Portrait Image Synthesis](https://arxiv.org/pdf/2207.10257.pdf)||
- Torch - NeRF: Neural Radiance Fields from Blurry Images](https://openaccess.thecvf.com/content/CVPR2022/papers/Ma_Deblur-NeRF_Neural_Radiance_Fields_From_Blurry_Images_CVPR_2022_paper.pdf)|
- NAN: Noise-Aware NeRFs for Burst-Denoising - aware-nerf.github.io/)|
- NeRF in the Dark: High Dynamic Range View Synthesis from Noisy Raw Images
- AR-NeRF: Unsupervised Learning of Depth and Defocus Effects from Natural Images with Aperture Rendering Neural Radiance Fields - nerf/)|
- Torch - view Stereo](https://openaccess.thecvf.com/content/ICCV2021/papers/Wei_NerfingMVS_Guided_Optimization_of_Neural_Radiance_Fields_for_Indoor_Multi-View_ICCV_2021_paper.pdf)|
- Torch - wei-liu.github.io/DeVRF/)|
- Decomposing NeRF for Editing via Feature Field Distillation - research.github.io/distilled-feature-fields/)|
- CageNeRF: Cage-based Neural Radiance Field for Generalized 3D Deformation and Animation
- Comming Soon - nerf/)|
- Torch
- NeRF in the Dark: High Dynamic Range View Synthesis from Noisy Raw Images
- AR-NeRF: Unsupervised Learning of Depth and Defocus Effects from Natural Images with Aperture Rendering Neural Radiance Fields - nerf/)|
- Torch - view Stereo](https://openaccess.thecvf.com/content/ICCV2021/papers/Wei_NerfingMVS_Guided_Optimization_of_Neural_Radiance_Fields_for_Indoor_Multi-View_ICCV_2021_paper.pdf)|
- Torch - wei-liu.github.io/DeVRF/)|
- Decomposing NeRF for Editing via Feature Field Distillation - research.github.io/distilled-feature-fields/)|
- CageNeRF: Cage-based Neural Radiance Field for Generalized 3D Deformation and Animation
- Comming Soon - nerf/)|
- Torch
- Torch - NeRF: Neural Inverse Rendering for Multi-view Photometric Stereo](https://ywq.github.io/psnerf/)|[Project Page](https://ywq.github.io/psnerf/)|
- Torch - based Implicit Field for Geometry and Texture Editing](https://arxiv.org/pdf/2207.11911.pdf)|[Project Page](https://zju3dv.github.io/neumesh/)|
- Torch - time and Accurate Neural Radiance Fields with Deterministic Integration for Volume Rendering](https://openaccess.thecvf.com/content/CVPR2022/papers/Wu_DIVeR_Real-Time_and_Accurate_Neural_Radiance_Fields_With_Deterministic_Integration_CVPR_2022_paper.pdf)|
- Torch - NeRF: Neural Radiance Fields from Blurry Images](https://openaccess.thecvf.com/content/CVPR2022/papers/Ma_Deblur-NeRF_Neural_Radiance_Fields_From_Blurry_Images_CVPR_2022_paper.pdf)|
- Jittor - Editing: Geometry Editing of Neural Radiance Fields](https://openaccess.thecvf.com/content/CVPR2022/papers/Yuan_NeRF-Editing_Geometry_Editing_of_Neural_Radiance_Fields_CVPR_2022_paper.pdf)|
- NAN: Noise-Aware NeRFs for Burst-Denoising - aware-nerf.github.io/)|
- Torch
- RigNeRF: Fully Controllable Neural 3D Portraits
- CoNeRF: Controllable Neural Radiance Fields
- Torch - Compositional Neural Radiance Field for Editable Scene Rendering](https://openaccess.thecvf.com/content/ICCV2021/papers/Yang_Learning_Object-Compositional_Neural_Radiance_Field_for_Editable_Scene_Rendering_ICCV_2021_paper.pdf)|[Project Page](https://zju3dv.github.io/object_nerf/)|
- Torch
- Torch - niemeyer.github.io/project-pages/giraffe/index.html)|
- Torch
- Torch - Paper.pdf)|[Project Page](https://www.guandaoyang.com/NFGP/)|
- Generative Neural Articulated Radiance Fields
- Torch - Shot Talking Head Synthesis](https://arxiv.org/pdf/2207.11770.pdf)|[Project Page](https://sstzal.github.io/DFRF/)|
- Torch - Aligned Neural Radiance Fields for Controllable 3D Human Synthesis](https://openaccess.thecvf.com/content/CVPR2022/papers/Xu_Surface-Aligned_Neural_Radiance_Fields_for_Controllable_3D_Human_Synthesis_CVPR_2022_paper.pdf)|
- Torch - viewpoint Rendering of Moving People from Monocular Video](https://openaccess.thecvf.com/content/CVPR2022/papers/Weng_HumanNeRF_Free-Viewpoint_Rendering_of_Moving_People_From_Monocular_Video_CVPR_2022_paper.pdf)|
- DoubleField: Bridging the Neural Surface and Radiance Fields for High-fidelity Human Reconstruction and Rendering
- Torch
- Torch
- Editable Free-Viewpoint Video using a Layered Neural Representation
- Torch - aware 3D Generative Adversarial Networks](https://openaccess.thecvf.com/content/CVPR2022/papers/Chan_Efficient_Geometry-Aware_3D_Generative_Adversarial_Networks_CVPR_2022_paper.pdf)|[Project Page](https://nvlabs.github.io/eg3d/)|
- Torch - Aware Image Synthesis](https://proceedings.neurips.cc/paper/2020/file/e92e1b476bb5262d793fd40931e0ed53-Paper.pdf)||
- Code - NeRF: Text-and-Image Driven Manipulation of Neural Radiance Fields](https://openaccess.thecvf.com/content/CVPR2022/papers/Wang_CLIP-NeRF_Text-and-Image_Driven_Manipulation_of_Neural_Radiance_Fields_CVPR_2022_paper.pdf)||
- Torch - inf.mpg.de/NeRF-OSR/)|
- Torch - Scale Scene Reconstruction](https://openaccess.thecvf.com/content/CVPR2022/papers/Zhang_NeRFusion_Fusing_Radiance_Fields_for_Large-Scale_Scene_Reconstruction_CVPR_2022_paper.pdf)|
- Mega-NeRF: Scalable Construction of Large-Scale NeRFs for Virtual Fly-Throughs
- Block-NeRF: Scalable Large Scene Neural View Synthesis
- Torch
- Torch - gsn/)|
- NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections - w.github.io/)|
- BARF: Bundle-Adjusting Neural Radiance Fields - adjusting-NeRF/)|
- Reinforcement Learning with Neural Radiance Fields - rl/)|
- TF - nerd/)|
- NeRV: Neural Reflectance and Visibility Fields for Relighting and View Synthesis
- TF
- Unsupervised Multi-View Object Segmentation Using Radiance Field Propagation
- LaTeRF: Label and Text Driven Object Radiance Fields
- Torch
- Jittor - 3D Mutual Learning](https://openaccess.thecvf.com/content/CVPR2022/papers/Huang_StylizedNeRF_Consistent_3D_Scene_Stylization_As_Stylized_NeRF_via_2D-3D_CVPR_2022_paper.pdf)|
- Torch
- Torch - view Reconstruction](https://arxiv.org/pdf/2106.10689.pdf)|[Project Page](https://lingjie0206.github.io/papers/NeuS/)|
- Volume Rendering of Neural Implicit Surfaces
- Torch - View Semantic Masks to Neural Radiance Fields](https://arxiv.org/pdf/2203.10821.pdf)|[Project Page](https://donydchen.github.io/sem2nerf/)|
- LOLNeRF: Learn from One Look - vision.github.io/lolnerf/)|
- Torch - time NeRF-based Parametric Head Model](https://openaccess.thecvf.com/content/CVPR2022/papers/Hong_HeadNeRF_A_Real-Time_NeRF-Based_Parametric_Head_Model_CVPR_2022_paper.pdf)|
- Torch - GAN for Single Image to NeuralRadiance Fields Translation](https://openaccess.thecvf.com/content/CVPR2022/papers/Cai_Pix2NeRF_Unsupervised_Conditional_p-GAN_for_Single_Image_to_Neural_Radiance_CVPR_2022_paper.pdf)|
- Torch - NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis](https://openaccess.thecvf.com/content/ICCV2021/papers/Guo_AD-NeRF_Audio_Driven_Neural_Radiance_Fields_for_Talking_Head_Synthesis_ICCV_2021_paper.pdf)|
- Comming Soon - Plenoxels: Self-Calibrating High Dynamic Range Radiance Fields](https://arxiv.org/pdf/2208.06787.pdf)||
- HDR-NeRF: High Dynamic Range Neural Radiance Fields
- Torch - based Volumetric Avatars using Relative Spatial Encoding of Keypoints](https://www.research-collection.ethz.ch/bitstream/handle/20.500.11850/563568/1322.pdf?sequence=1)|[Project Page](https://markomih.github.io/KeypointNeRF/)|
- Torch
- Structured Local Radiance Fields for Human Avatar Modeling
- Torch - Aligned Neural Radiance Fields for Controllable 3D Human Synthesis](https://openaccess.thecvf.com/content/CVPR2022/papers/Xu_Surface-Aligned_Neural_Radiance_Fields_for_Controllable_3D_Human_Synthesis_CVPR_2022_paper.pdf)|
- Torch - viewpoint Rendering of Moving People from Monocular Video](https://openaccess.thecvf.com/content/CVPR2022/papers/Weng_HumanNeRF_Free-Viewpoint_Rendering_of_Moving_People_From_Monocular_Video_CVPR_2022_paper.pdf)|
- DoubleField: Bridging the Neural Surface and Radiance Fields for High-fidelity Human Reconstruction and Rendering
- Torch
- Torch
- Editable Free-Viewpoint Video using a Layered Neural Representation
- Torch - aware 3D Generative Adversarial Networks](https://openaccess.thecvf.com/content/CVPR2022/papers/Chan_Efficient_Geometry-Aware_3D_Generative_Adversarial_Networks_CVPR_2022_paper.pdf)|[Project Page](https://nvlabs.github.io/eg3d/)|
- Torch - Aware Image Synthesis](https://proceedings.neurips.cc/paper/2020/file/e92e1b476bb5262d793fd40931e0ed53-Paper.pdf)||
- Code - NeRF: Text-and-Image Driven Manipulation of Neural Radiance Fields](https://openaccess.thecvf.com/content/CVPR2022/papers/Wang_CLIP-NeRF_Text-and-Image_Driven_Manipulation_of_Neural_Radiance_Fields_CVPR_2022_paper.pdf)||
- Torch - inf.mpg.de/NeRF-OSR/)|
- HDR-NeRF: High Dynamic Range Neural Radiance Fields
- Geometry-Guided Progressive NeRF for Generalizable and Efficient Neural Human Rendering
- Torch - based Volumetric Avatars using Relative Spatial Encoding of Keypoints](https://www.research-collection.ethz.ch/bitstream/handle/20.500.11850/563568/1322.pdf?sequence=1)|[Project Page](https://markomih.github.io/KeypointNeRF/)|
- Torch
- Structured Local Radiance Fields for Human Avatar Modeling
- Torch - Scale Scene Reconstruction](https://openaccess.thecvf.com/content/CVPR2022/papers/Zhang_NeRFusion_Fusing_Radiance_Fields_for_Large-Scale_Scene_Reconstruction_CVPR_2022_paper.pdf)|
- Mega-NeRF: Scalable Construction of Large-Scale NeRFs for Virtual Fly-Throughs
- Block-NeRF: Scalable Large Scene Neural View Synthesis
- Torch
- Torch - gsn/)|
- NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections - w.github.io/)|
- BARF: Bundle-Adjusting Neural Radiance Fields - adjusting-NeRF/)|
- Reinforcement Learning with Neural Radiance Fields - rl/)|
- Factorized and Controllable Neural Re-Rendering of Outdoor Scene for Photo Extrapolation
- TF - nerd/)|
- NeRV: Neural Reflectance and Visibility Fields for Relighting and View Synthesis
- TF
- Unsupervised Multi-View Object Segmentation Using Radiance Field Propagation
- LaTeRF: Label and Text Driven Object Radiance Fields
- Torch
- Jittor - 3D Mutual Learning](https://openaccess.thecvf.com/content/CVPR2022/papers/Huang_StylizedNeRF_Consistent_3D_Scene_Stylization_As_Stylized_NeRF_via_2D-3D_CVPR_2022_paper.pdf)|
- Torch
- Torch - View Reconstruction](https://openaccess.thecvf.com/content/ICCV2021/papers/Oechsle_UNISURF_Unifying_Neural_Implicit_Surfaces_and_Radiance_Fields_for_Multi-View_ICCV_2021_paper.pdf)|
- Torch - view Reconstruction](https://arxiv.org/pdf/2106.10689.pdf)|[Project Page](https://lingjie0206.github.io/papers/NeuS/)|
- Volume Rendering of Neural Implicit Surfaces
- TF - Dimensional Representation for Topologically Varying Neural Radiance Fields](https://arxiv.org/pdf/2106.13228.pdf)|[Project Page](https://hypernerf.github.io/)|
- Torch - NeRF: Neural Radiance Fields for Dynamic Scenes](https://openaccess.thecvf.com/content/CVPR2021/papers/Pumarola_D-NeRF_Neural_Radiance_Fields_for_Dynamic_Scenes_CVPR_2021_paper.pdf)|
- Torch - Rigid Neural Radiance Fields: Reconstruction and Novel View Synthesis of a Dynamic Scene From Monocular Video](https://openaccess.thecvf.com/content/ICCV2021/papers/Tretschk_Non-Rigid_Neural_Radiance_Fields_Reconstruction_and_Novel_View_Synthesis_of_ICCV_2021_paper.pdf)|
- Learning Compositional Radiance Fields of Dynamic Human Heads
- Space-time Neural Irradiance Fields for Free-Viewpoint Video - nerf.github.io/)
- Ray Priors through Reprojection: Improving Neural Radiance Fields for Novel View Extrapolation
- TF - Dimensional Representation for Topologically Varying Neural Radiance Fields](https://arxiv.org/pdf/2106.13228.pdf)|[Project Page](https://hypernerf.github.io/)|
- Torch - NeRF: Neural Radiance Fields for Dynamic Scenes](https://openaccess.thecvf.com/content/CVPR2021/papers/Pumarola_D-NeRF_Neural_Radiance_Fields_for_Dynamic_Scenes_CVPR_2021_paper.pdf)|
- Torch - Rigid Neural Radiance Fields: Reconstruction and Novel View Synthesis of a Dynamic Scene From Monocular Video](https://openaccess.thecvf.com/content/ICCV2021/papers/Tretschk_Non-Rigid_Neural_Radiance_Fields_Reconstruction_and_Novel_View_Synthesis_of_ICCV_2021_paper.pdf)|
- Learning Compositional Radiance Fields of Dynamic Human Heads
- Space-time Neural Irradiance Fields for Free-Viewpoint Video - nerf.github.io/)
- Ray Priors through Reprojection: Improving Neural Radiance Fields for Novel View Extrapolation
- Generative Neural Articulated Radiance Fields
- Torch
- Torch
- TF - Supervised Decoupling of Dynamic and Static Objects from a Monocular Video](https://arxiv.org/pdf/2205.15838.pdf)|[Project Page](https://d2nerf.github.io/)|
-
NeRF
- TF - pytorch)|[NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis](https://dl.acm.org/doi/pdf/10.1145/3503250)|
- Conditional-Flow NeRF: Accurate 3D Modelling with Reliable Uncertainty Quantification
- Comming Soon
- Torch - group.github.io/SinNeRF/)|
- Dense Depth Priors for Neural Radiance Fields from Sparse Input Views
- TF
- AutoRF: Learning 3D Object Radiance Fields from Single View Observation
- Torch - Shot Neural Volume Rendering](https://openaccess.thecvf.com/content/CVPR2022/papers/Kim_InfoNeRF_Ray_Entropy_Minimization_for_Few-Shot_Neural_Volume_Rendering_CVPR_2022_paper.pdf)|
- Torch - supervised NeRF: Fewer Views and Faster Training for Free](https://openaccess.thecvf.com/content/CVPR2022/papers/Deng_Depth-Supervised_NeRF_Fewer_Views_and_Faster_Training_for_Free_CVPR_2022_paper.pdf)|
- Torch - Shot View Synthesis](https://openaccess.thecvf.com/content/ICCV2021/papers/Jain_Putting_NeRF_on_a_Diet_Semantically_Consistent_Few-Shot_View_Synthesis_ICCV_2021_paper.pdf)|[Project Page](https://www.ajayj.com/dietnerf)|
- Torch
- Torch - View Stereo](https://openaccess.thecvf.com/content/ICCV2021/papers/Chen_MVSNeRF_Fast_Generalizable_Radiance_Field_Reconstruction_From_Multi-View_Stereo_ICCV_2021_paper.pdf)|[Project Page](https://apchenstu.github.io/mvsnerf/)|
- Torch
- JAX - nerf.github.io/)|
- TF
- AutoRF: Learning 3D Object Radiance Fields from Single View Observation
- GeoAug: Data Augmentation for Few-Shot NeRF with Geometry Constrains
- GeoAug: Data Augmentation for Few-Shot NeRF with Geometry Constrains
- Torch - Sim: Learning to Generate Training Data with NeRF](https://arxiv.org/pdf/2207.11368.pdf)||
- Torch - Sim: Learning to Generate Training Data with NeRF](https://arxiv.org/pdf/2207.11368.pdf)||
- Torch - NeRF: Training Stronger Neural Radiance Fields with Triple-Level Physically-Grounded Augmentations](https://openaccess.thecvf.com/content/CVPR2022/papers/Chen_Aug-NeRF_Training_Stronger_Neural_Radiance_Fields_With_Triple-Level_Physically-Grounded_Augmentations_CVPR_2022_paper.pdf)|
- Torch - NeRF: Training Stronger Neural Radiance Fields with Triple-Level Physically-Grounded Augmentations](https://openaccess.thecvf.com/content/CVPR2022/papers/Chen_Aug-NeRF_Training_Stronger_Neural_Radiance_Fields_With_Triple-Level_Physically-Grounded_Augmentations_CVPR_2022_paper.pdf)|
- TF - Supervised Decoupling of Dynamic and Static Objects from a Monocular Video](https://arxiv.org/pdf/2205.15838.pdf)|[Project Page](https://d2nerf.github.io/)|
- TF - Supervised Decoupling of Dynamic and Static Objects from a Monocular Video](https://arxiv.org/pdf/2205.15838.pdf)|[Project Page](https://d2nerf.github.io/)|
- Comming Soon
- Torch - group.github.io/SinNeRF/)|
- Dense Depth Priors for Neural Radiance Fields from Sparse Input Views
- Torch - Shot Neural Volume Rendering](https://openaccess.thecvf.com/content/CVPR2022/papers/Kim_InfoNeRF_Ray_Entropy_Minimization_for_Few-Shot_Neural_Volume_Rendering_CVPR_2022_paper.pdf)|
- Torch - supervised NeRF: Fewer Views and Faster Training for Free](https://openaccess.thecvf.com/content/CVPR2022/papers/Deng_Depth-Supervised_NeRF_Fewer_Views_and_Faster_Training_for_Free_CVPR_2022_paper.pdf)|
- Torch - Shot View Synthesis](https://openaccess.thecvf.com/content/ICCV2021/papers/Jain_Putting_NeRF_on_a_Diet_Semantically_Consistent_Few-Shot_View_Synthesis_ICCV_2021_paper.pdf)|[Project Page](https://www.ajayj.com/dietnerf)|
- Torch
- Torch - View Stereo](https://openaccess.thecvf.com/content/ICCV2021/papers/Chen_MVSNeRF_Fast_Generalizable_Radiance_Field_Reconstruction_From_Multi-View_Stereo_ICCV_2021_paper.pdf)|[Project Page](https://apchenstu.github.io/mvsnerf/)|
- Torch
- JAX - nerf.github.io/)|
- Torch - composable NeRF via Rank-residual Decomposition](https://arxiv.org/pdf/2205.14870.pdf)||
- Neural Transmitted Radiance Fields
- Torch
- Jax - Skip Transformer](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136920069.pdf)||
- Torch - research.github.io/R2L/)|
- Gaussian Activated Neural Radiance Fields for High Fidelity Reconstruction & Pose Estimation
- Conditional-Flow NeRF: Accurate 3D Modelling with Reliable Uncertainty Quantification
- Torch - free Neural Rendering from Few Images Using Transformers](https://arxiv.org/pdf/2203.10157.pdf)||
- Fourier PlenOctrees for Dynamic Radiance Field Rendering in Real-time
- Torch - composable NeRF via Rank-residual Decomposition](https://arxiv.org/pdf/2205.14870.pdf)||
- Neural Transmitted Radiance Fields
- Torch
- Jax - Skip Transformer](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136920069.pdf)||
- Torch - research.github.io/R2L/)|
- Gaussian Activated Neural Radiance Fields for High Fidelity Reconstruction & Pose Estimation
- Conditional-Flow NeRF: Accurate 3D Modelling with Reliable Uncertainty Quantification
- Torch - free Neural Rendering from Few Images Using Transformers](https://arxiv.org/pdf/2203.10157.pdf)||
- Gaussian Activated Neural Radiance Fields for High Fidelity Reconstruction & Pose Estimation
- Gaussian Activated Neural Radiance Fields for High Fidelity Reconstruction & Pose Estimation
- Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fields
- Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fields
- Urban Radiance Fields
- Torch
- Torch
- NeRFReN: Neural Radiance Fields with Reflections
- Torch - based Neural Radiance Field without Posed Camera](https://openaccess.thecvf.com/content/ICCV2021/papers/Meng_GNeRF_GAN-Based_Neural_Radiance_Field_Without_Posed_Camera_ICCV_2021_paper.pdf)|
- TF
- TF
- Code - ngp/)|
- Code - ngp/)|
- Torch - time Rendering of Neural Radiance Fields](https://arxiv.org/pdf/2207.10312v1.pdf)|
- Torch - NeRF: Point-based Neural Radiance Fields](https://openaccess.thecvf.com/content/CVPR2022/papers/Xu_Point-NeRF_Point-Based_Neural_Radiance_Fields_CVPR_2022_paper.pdf)|
- Fourier PlenOctrees for Dynamic Radiance Field Rendering in Real-time
- Torch - fast Convergence for Radiance Fields Reconstruction](https://openaccess.thecvf.com/content/CVPR2022/papers/Sun_Direct_Voxel_Grid_Optimization_Super-Fast_Convergence_for_Radiance_Fields_Reconstruction_CVPR_2022_paper.pdf)|[Project Page](https://sunset1995.github.io/dvgo/)|
- Torch
- Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fields
- TF - NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields](https://openaccess.thecvf.com/content/ICCV2021/papers/Barron_Mip-NeRF_A_Multiscale_Representation_for_Anti-Aliasing_Neural_Radiance_Fields_ICCV_2021_paper.pdf)|
- Torch - time Rendering of Neural Radiance Fields](https://openaccess.thecvf.com/content/ICCV2021/papers/Yu_PlenOctrees_for_Real-Time_Rendering_of_Neural_Radiance_Fields_ICCV_2021_paper.pdf)|[Project Page](https://alexyu.net/plenoctrees/)|
- Torch
- TF - vision.github.io/derf/)|
- Torch - fast Convergence for Radiance Fields Reconstruction](https://openaccess.thecvf.com/content/CVPR2022/papers/Sun_Direct_Voxel_Grid_Optimization_Super-Fast_Convergence_for_Radiance_Fields_Reconstruction_CVPR_2022_paper.pdf)|[Project Page](https://sunset1995.github.io/dvgo/)|
- Torch
- Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fields
- TF - NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields](https://openaccess.thecvf.com/content/ICCV2021/papers/Barron_Mip-NeRF_A_Multiscale_Representation_for_Anti-Aliasing_Neural_Radiance_Fields_ICCV_2021_paper.pdf)|
- Torch - time Rendering of Neural Radiance Fields](https://openaccess.thecvf.com/content/ICCV2021/papers/Yu_PlenOctrees_for_Real-Time_Rendering_of_Neural_Radiance_Fields_ICCV_2021_paper.pdf)|[Project Page](https://alexyu.net/plenoctrees/)|
- Torch
- TF - Time View Synthesis](https://openaccess.thecvf.com/content/ICCV2021/papers/Hedman_Baking_Neural_Radiance_Fields_for_Real-Time_View_Synthesis_ICCV_2021_paper.pdf)|[Project Page](https://phog.github.io/snerg/)|
-
Survey
- NeRF: Neural Radiance Field in 3D Vision, A Comprehensive Review
- Neural Fields in Visual Computing and Beyond
- Advances in Neural Rendering
- NeRF: Neural Radiance Field in 3D Vision, A Comprehensive Review
- State of the Art on Neural Rendering
- State of the Art on Neural Rendering
- Advances in Neural Rendering
- NeRF: Neural Radiance Field in 3D Vision, A Comprehensive Review
- Neural Fields in Visual Computing and Beyond
-
Unclassified
- BungeeNeRF: Progressive Neural Radiance Field for Extreme Multiscale Scene Rendering
- Neural Volumetric Object Selection
- Torch
- BungeeNeRF: Progressive Neural Radiance Field for Extreme Multiscale Scene Rendering
- Neural Volumetric Object Selection
- Torch
- Torch - Calibrating Neural Radiance Fields](https://openaccess.thecvf.com/content/ICCV2021/papers/Jeong_Self-Calibrating_Neural_Radiance_Fields_ICCV_2021_paper.pdf)|
- Torch - Calibrating Neural Radiance Fields](https://openaccess.thecvf.com/content/ICCV2021/papers/Jeong_Self-Calibrating_Neural_Radiance_Fields_ICCV_2021_paper.pdf)|
-
-
Talks
-
Unclassified
- Michael Niemeyer: Generative Neural Scene Representations 3D Representation Seminar - Chen Lin|EN|
- NeRFactor: Neural Factorization of Shape and Reflectance Under an Unknown Illumination
- NeRD: Neural Reflectance Decomposition from Image Collections
- NeRF: Neural Radiance Fields
- NeRF及其发展
- NeRF at CVPR 2022
- NeRF at ICCV 2021
- NeRF Explosion 2020 - ->
- TensoRF: Tensorial Radiance Fields
- ECCV2022 - Learning Dynamic Facial Radiance Fields for Few-Shot Talking Head Synthesis
- [NeRF-OSR, ECCV 2022
- PS-NeRF: Neural Inverse Rendering for Multi-view Photometric Stereo (ECCV 2022)
- [ECCV 2022
- [ECCV'22
- [CVPR 2022
- [ACM-MM'22
- Geometry Processing with Neural Fields
- Editing Conditional Radiance Fields
- Michael Niemeyer: Generative Neural Scene Representations 3D Representation Seminar - Chen Lin|EN|
- NeRFactor: Neural Factorization of Shape and Reflectance Under an Unknown Illumination
- NeRD: Neural Reflectance Decomposition from Image Collections
- NeRF: Neural Radiance Fields
- NeRF及其发展
- NeRF at CVPR 2022
- NeRF at ICCV 2021
- NeRF Explosion 2020 - ->
- TensoRF: Tensorial Radiance Fields
- ECCV2022 - Learning Dynamic Facial Radiance Fields for Few-Shot Talking Head Synthesis
- [NeRF-OSR, ECCV 2022
- PS-NeRF: Neural Inverse Rendering for Multi-view Photometric Stereo (ECCV 2022)
- [ECCV 2022
- [ECCV'22
- [CVPR 2022
- [ACM-MM'22
- Geometry Processing with Neural Fields
- Editing Conditional Radiance Fields
-
-
Team
-
Team Members
-
Contributors
-
-
Datasets
-
Unclassified
- PeRFception - 0J)|2D classification, 3D classification, 3D segmentation|19k||
- NeuS-DATA - view Reconstruction](https://arxiv.org/pdf/2106.10689.pdf)|Surface Reconstruction|-||
- NeRF-DATA - |Benchmark|
- PeRFception - 0J)|2D classification, 3D classification, 3D segmentation|19k||
- NeuS-DATA - view Reconstruction](https://arxiv.org/pdf/2106.10689.pdf)|Surface Reconstruction|-||
- NeRF-DATA - |Benchmark|
-
-
Acknowledgment
-
Unclassified
- repo - NeRF](https://github.com/koolo233/awesome-NeRF). Some features were borrowed from [repo](https://github.com/yenchenlin/awesome-NeRF), so we are grateful for their works.
-
Programming Languages
Categories
Sub Categories
Keywords
nerf
42
neural-rendering
15
3d-reconstruction
13
neural-radiance-fields
12
machine-learning
10
pytorch
10
computer-vision
10
3d
9
deep-learning
8
neural-network
8
novel-view-synthesis
6
3d-vision
6
eccv2022
6
cvpr2022
5
relighting
4
reflectance
4
illumination
4
generative-adversarial-network
4
gan
3
volume-rendering
3
image-to-image
2
image-manipulation
2
image-generation
2
eccv-2022
2
image-translation
2
view-synthesis
2
semantic-to-nerf
2
adversarial-robustness
2
3d-modelling
2
3d-rendering
2
distillation
2
mlp
2
neural-light-field
2
depth-estimation
2
self-calibration
2
dsnerf
2
implicit-representions
2
calibration
2
cvpr2021
2
generative-model
2
generative-modelling
2
implicit-surfaces
2
neural-scene-representations
2
geometry-processing
2
jittor
2
neural-fields
2
3d-aware-image-synthesis
2
image-to-image-translation
2
stylegan2
2
vr
2