{"id":76300,"url":"https://github.com/MatrixBrain/awesome-NeRF","name":"awesome-NeRF","description":"A curated list of awesome neural radiance fields (NeRF) papers.","projects_count":171,"last_synced_at":"2026-07-13T15:00:22.181Z","repository":{"id":61345248,"uuid":"538532810","full_name":"MatrixBrain/awesome-NeRF","owner":"MatrixBrain","description":"A curated list of awesome neural radiance fields (NeRF) papers.","archived":false,"fork":false,"pushed_at":"2023-01-30T10:11:34.000Z","size":106,"stargazers_count":228,"open_issues_count":0,"forks_count":15,"subscribers_count":10,"default_branch":"main","last_synced_at":"2026-06-25T09:02:32.949Z","etag":null,"topics":["3d-reconstruction","awesome-list","awesome-nerf","depth-estimation","nerf","neural-implicit-representations","neural-radiance-fields","neural-rendering","novel-view-synthesis","pose-estimation"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/MatrixBrain.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2022-09-19T14:06:31.000Z","updated_at":"2026-06-17T10:12:57.000Z","dependencies_parsed_at":"2023-02-16T06:15:53.654Z","dependency_job_id":null,"html_url":"https://github.com/MatrixBrain/awesome-NeRF","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/MatrixBrain/awesome-NeRF","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MatrixBrain%2Fawesome-NeRF","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MatrixBrain%2Fawesome-NeRF/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MatrixBrain%2Fawesome-NeRF/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MatrixBrain%2Fawesome-NeRF/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/MatrixBrain","download_url":"https://codeload.github.com/MatrixBrain/awesome-NeRF/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/MatrixBrain%2Fawesome-NeRF/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":35426086,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-07-13T02:00:06.543Z","response_time":119,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"created_at":"2024-11-07T03:25:54.043Z","updated_at":"2026-07-13T15:00:22.182Z","primary_language":null,"list_of_lists":false,"displayable":true,"categories":["Papers","Talks","Datasets","Team","Acknowledgment"],"sub_categories":["NeRF Related Tasks","NeRF","Unclassified","Survey","Team Members","Contributors"],"readme":"# Awesome Neural Radiance Fields (NeRF) [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)\nA curated list of awesome neural radiance fields (NeRF) papers. All papers are grouped according to keywords/tasks, and sorted by year. We hope this review can help peers who are interested in conducting NeRF related research.\n\n## Contributing\nWarmly welcome everyone to participate in this project!!! If you are interested in joining our team and organizing NeRF related papers/codes/projects together, please submit PR according to the following guide. We'll put your name on the list of contributors.\n\n\n[Submit a Pull Request](./submit-pr.md)\n\n## Table of Contents\n\n- [Papers](#Papers)\n    - [Survey](#survey)\n    - [NeRF](#nerf)\n        - [Data Augmentation](#data-augmentation)\n        - [Few shot](#few-shot)\n        - [Rendering Performance](#rendering-performance)\n        - [Theory](#theory)\n        - [Training \u0026 Inference Efficiency](#training--inference-efficiency)\n    - [NeRF Related Tasks](#nerf-related-tasks)\n        - [Deblur \u0026 Denoise](#deblur--denoise)\n        - [Depth Estimation](#depth-estimation)\n        - [Editing](#editing)\n        - [Face](#face)\n        - [High Dynamic Range (HDR)](#high-dynamic-range-hdr)\n        - [Human](#human)\n        - [Image Generation](#image-generation)\n            - [Image Generation](#image-generation-1)\n            - [Text \u0026 Image Guided Generation](#text--image-guided-generation)\n        - [Large Scale Scene](#large-scale-scene)\n        - [Pose Misalignment](#pose-misalignment)\n        - [Reinforcement Learning]()\n        - [Relighting](#relighting)\n        - [Segmentation](#segmentation)\n        - [Stylized](#stylized)\n        - [Surface Reconstruction](#surface-reconstruction)\n        - [Video](#video)\n        - [View Synthesis Extrapolation](#view-synthesis-extrapolation)\n    - [Unclassified](#unclassified)\n- [Datasets](#datasets)\n- [Talks](#talks)\n- [Acknowledgment](#acknowledgment)\n- [Team](#team)\n\u003c!-- - [Blogs](#blogs) --\u003e\n\n\n## Papers\n\n|Year|Conf/Jour|Code|Title|OtherInfo|\n|:-:|:-:|:-:|:-:|:-:|\n|2020|ECCV|[TF](https://github.com/bmild/nerf) [Torch](https://github.com/yenchenlin/nerf-pytorch)|[NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis](https://dl.acm.org/doi/pdf/10.1145/3503250)|[Project Page](https://www.matthewtancik.com/nerf)|\n\n### Survey\n\n|Year|Conf/Jour|Code|Title|OtherInfo|\n|:-:|:-:|:-:|:-:|:-:|\n|2022|Computer Graphics Forum||[Advances in Neural Rendering](https://arxiv.org/pdf/2111.05849.pdf)||\n|2022|-||[NeRF: Neural Radiance Field in 3D Vision, A Comprehensive Review](https://arxiv.org/pdf/2210.00379.pdf)||\n|2022|Computer Graphics Forum||[Neural Fields in Visual Computing and Beyond](https://arxiv.org/pdf/2111.11426.pdf)||\n|2020|Computer Graphics Forum||[State of the Art on Neural Rendering](https://onlinelibrary.wiley.com/doi/am-pdf/10.1111/cgf.14022)||\n\n### NeRF\n\n#### Data Augmentation\n\n|Year|Conf/Jour|Code|Title|OtherInfo|\n|:-:|:-:|:-:|:-:|:-:|\n|2022|ECCV||[GeoAug: Data Augmentation for Few-Shot NeRF with Geometry Constrains](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136770326.pdf)|\n|2022|ECCV|[Torch](https://github.com/gyhandy/Neural-Sim-NeRF)|[Neural-Sim: Learning to Generate Training Data with NeRF](https://arxiv.org/pdf/2207.11368.pdf)||\n|2022|CVPR|[Torch](https://github.com/VITA-Group/Aug-NeRF)|[Aug-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)|\n\n#### Few Shot\n\n|Year|Conf/Jour|Code|Title|OtherInfo|\n|:-:|:-:|:-:|:-:|:-:|\n|2022|NeurIPS|[TF](https://github.com/d2nerf/d2nerf)|[D^2NeRF: Self-Supervised Decoupling of Dynamic and Static Objects from a Monocular Video](https://arxiv.org/pdf/2205.15838.pdf)|[Project Page](https://d2nerf.github.io/)|\n|2022|ECCV|[Comming Soon](https://github.com/LeapLabTHU/ActiveNeRF)|[ActiveNeRF: Learning where to See with Uncertainty Estimation](https://arxiv.org/pdf/2209.08546.pdf)||\n|2022|ECCV||[GeoAug: Data Augmentation for Few-Shot NeRF with Geometry Constrains](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136770326.pdf)|\n|2022|ECCV|[Torch](https://github.com/VITA-Group/SinNeRF/blob/master/requirements.txt)|[SinNeRF: Training Neural Radiance Fields on Complex Scenes from a Single Image](https://arxiv.org/pdf/2204.00928.pdf)|[Project Page](https://vita-group.github.io/SinNeRF/)|\n|2022|CVPR||[Dense Depth Priors for Neural Radiance Fields from Sparse Input Views](https://openaccess.thecvf.com/content/CVPR2022/papers/Roessle_Dense_Depth_Priors_for_Neural_Radiance_Fields_From_Sparse_Input_CVPR_2022_paper.pdf)|\n|2022|CVPR|[TF](https://m-niemeyer.github.io/regnerf)|[RegNeRF: Regularizing Neural Radiance Fields for View Synthesis from Sparse Inputs](https://openaccess.thecvf.com/content/CVPR2022/papers/Niemeyer_RegNeRF_Regularizing_Neural_Radiance_Fields_for_View_Synthesis_From_Sparse_CVPR_2022_paper.pdf)|\n|2022|CVPR||[AutoRF: Learning 3D Object Radiance Fields from Single View Observation](https://openaccess.thecvf.com/content/CVPR2022/papers/Muller_AutoRF_Learning_3D_Object_Radiance_Fields_From_Single_View_Observations_CVPR_2022_paper.pdf)|[Project Page](https://sirwyver.github.io/AutoRF/)|\n|2022|CVPR|[Torch](https://github.com/mjmjeong/InfoNeRF)|[InfoNeRF: Ray Entropy Minimization for Few-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)|\n|2022|CVPR|[Torch](https://github.com/dunbar12138/DSNeRF)|[Depth-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)|\n|2021|ICCV|[Torch](https://github.com/ajayjain/DietNeRF)|[Putting NeRF on a Diet: Semantically Consistent Few-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)|\n|2021|ICCV|[Torch](https://github.com/yilundu/nerflow)|[Neural Radiance Flow for 4D View Synthesis and Video Processing](https://openaccess.thecvf.com/content/ICCV2021/papers/Du_Neural_Radiance_Flow_for_4D_View_Synthesis_and_Video_Processing_ICCV_2021_paper.pdf)|\n|2021|ICCV|[Torch](https://github.com/apchenstu/mvsnerf)|[MVSNeRF: Fast Generalizable Radiance Field Reconstruction from Multi-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/)|\n|2021|CVPR|[Torch](https://github.com/sxyu/pixel-nerf)|[pixelNeRF: Neural Radiance Fields from One or Few Images](https://openaccess.thecvf.com/content/CVPR2021/papers/Yu_pixelNeRF_Neural_Radiance_Fields_From_One_or_Few_Images_CVPR_2021_paper.pdf)|[Project Page](https://alexyu.net/pixelnerf/)|\n\n#### Rendering Performance\n\n|Year|Conf/Jour|Code|Title|OtherInfo|\n|:-:|:-:|:-:|:-:|:-:|\n|2022|arXiv|[JAX](https://github.com/google-research/jax3d/tree/main/jax3d/projects/mobilenerf)|[MobileNeRF: Exploiting the Polygon Rasterization Pipeline for Efficient Neural Field Rendering on Mobile Architectures](https://arxiv.org/pdf/2208.00277.pdf)|[Project Page](https://mobile-nerf.github.io/)|\n|2022|NeurIPS|[Torch](https://github.com/ashawkey/CCNeRF)|[Compressible-composable NeRF via Rank-residual Decomposition](https://arxiv.org/pdf/2205.14870.pdf)||\n|2022|NeurIPS||[Neural Transmitted Radiance Fields](https://openreview.net/pdf?id=KglFYlTiASW)||\n|2022|ECCV|[Torch](https://github.com/apchenstu/TensoRF)|[TensoRF: Tensorial Radiance Fields](https://arxiv.org/pdf/2203.09517.pdf)|[Project Page](https://apchenstu.github.io/TensoRF/)|\n|2022|ECCV|[Jax](https://github.com/Crishawy/NeXT)|[NeXT: Towards High Quality Neural Radiance Fields via Multi-Skip Transformer](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136920069.pdf)||\n|2022|ECCV|[Torch](https://github.com/snap-research/R2L)|[R2L: Distilling Neural Radiance Field to Neural Light Field for Efficient Novel View Synthesis](https://arxiv.org/pdf/2203.17261.pdf)|[Project Page](https://snap-research.github.io/R2L/)|\n|2022|ECCV||[Gaussian Activated Neural Radiance Fields for High Fidelity Reconstruction \u0026 Pose Estimation](https://arxiv.org/pdf/2204.05735.pdf)||\n|2022|ECCV||[Conditional-Flow NeRF: Accurate 3D Modelling with Reliable Uncertainty Quantification](https://arxiv.org/pdf/2203.10192.pdf)||\n|2022|ECCV|[Torch](https://github.com/jkulhanek/viewformer/blob/master/requirements.txt)|[ViewFormer: NeRF-free Neural Rendering from Few Images Using Transformers](https://arxiv.org/pdf/2203.10157.pdf)||\n|2022|ECCV||[Gaussian Activated Neural Radiance Fields for High Fidelity Reconstruction \u0026 Pose Estimation](https://arxiv.org/pdf/2204.05735v1.pdf)|\n|2022|CVPR||[Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fields](https://openaccess.thecvf.com/content/CVPR2022/papers/Verbin_Ref-NeRF_Structured_View-Dependent_Appearance_for_Neural_Radiance_Fields_CVPR_2022_paper.pdf)|\n|2022|CVPR||[Urban Radiance Fields](https://openaccess.thecvf.com/content/CVPR2022/papers/Rematas_Urban_Radiance_Fields_CVPR_2022_paper.pdf)|\n|2022|CVPR|[Torch](https://github.com/idiap/GeoNeRF)|[GeoNeRF: Generalizing NeRF with Geometry Priors](https://openaccess.thecvf.com/content/CVPR2022/papers/Johari_GeoNeRF_Generalizing_NeRF_With_Geometry_Priors_CVPR_2022_paper.pdf)|[Project Page](https://www.idiap.ch/paper/geonerf/)|\n|2022|CVPR||[NeRFReN: Neural Radiance Fields with Reflections](https://openaccess.thecvf.com/content/CVPR2022/papers/Guo_NeRFReN_Neural_Radiance_Fields_With_Reflections_CVPR_2022_paper.pdf)|\n|2022|CVPR|[Torch](https://github.com/VITA-Group/Aug-NeRF)|[Aug-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)|\n|2021|ICCV|[Torch](https://github.com/quan-meng/gnerf)|[GNeRF: GAN-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)|\n|2021|ICCV|[Torch](https://github.com/autonomousvision/unisurf)|[UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-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)|\n|2021|ICCV|[Torch](https://github.com/vincentfung13/MINE)|[MINE: Towards Continuous Depth MPI with NeRF for Novel View Synthesis](https://openaccess.thecvf.com/content/ICCV2021/papers/Li_MINE_Towards_Continuous_Depth_MPI_With_NeRF_for_Novel_View_ICCV_2021_paper.pdf)|\n|2021|ICCV|[TF](https://github.com/google/nerfies)|[Nerfies: Deformable Neural Radiance Fields](https://openaccess.thecvf.com/content/ICCV2021/papers/Park_Nerfies_Deformable_Neural_Radiance_Fields_ICCV_2021_paper.pdf)|[Project Page](https://nerfies.github.io/)|\n\n#### Theory\n\n|Year|Conf/Jour|Code|Title|OtherInfo|\n|:-:|:-:|:-:|:-:|:-:|\n|2020|ECCV|[TF](https://github.com/bmild/nerf) [Torch](https://github.com/yenchenlin/nerf-pytorch)|[NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis](https://dl.acm.org/doi/pdf/10.1145/3503250)|\n\n#### Training \u0026 Inference Efficiency\n\n|Year|Conf/Jour|Code|Title|OtherInfo|\n|:-:|:-:|:-:|:-:|:-:|\n|2022|ACM TOG|[Code](https://github.com/NVlabs/instant-ngp)|[Instant Neural Graphics Primitives with a Multiresolution Hash Encoding](https://arxiv.org/pdf/2201.05989.pdf)|[Project Page](https://nvlabs.github.io/instant-ngp/)|\n|2022|ECCV|[Torch](https://github.com/snap-research/R2L)|[R2L: Distilling Neural Radiance Field to Neural Light Field for Efficient Novel View Synthesis](https://arxiv.org/pdf/2203.17261.pdf)|[Project Page](https://snap-research.github.io/R2L/)|\n|2022|ECCV||[Geometry-Guided Progressive NeRF for Generalizable and Efficient Neural Human Rendering](https://arxiv.org/pdf/2112.04312.pdf)||\n|2022|ECCV|[Torch](https://github.com/jkulhanek/viewformer/blob/master/requirements.txt)|[ViewFormer: NeRF-free Neural Rendering from Few Images Using Transformers](https://arxiv.org/pdf/2203.10157.pdf)||\n|2022|ECCV|[Torch](https://github.com/thomasneff/AdaNeRF)|[AdaNeRF: Adaptive Sampling for Real-time Rendering of Neural Radiance Fields](https://arxiv.org/pdf/2207.10312v1.pdf)|\n|2022|CVPR|[Torch](https://github.com/Xharlie/pointnerf)|[Point-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)|\n|2022|CVPR|[Torch](https://github.com/lwwu2/diver-rt)|[DIVeR: Real-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)|\n|2022|CVPR||[Fourier PlenOctrees for Dynamic Radiance Field Rendering in Real-time](https://openaccess.thecvf.com/content/CVPR2022/papers/Wang_Fourier_PlenOctrees_for_Dynamic_Radiance_Field_Rendering_in_Real-Time_CVPR_2022_paper.pdf)|\n|2022|CVPR|[Torch](https://github.com/sunset1995/DirectVoxGO)|[Direct Voxel Grid Optimization: Super-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/)|\n|2022|CVPR|[Torch](https://github.com/dvlab-research/EfficientNeRF)|[EfficientNeRF – Efficient Neural Radiance Fields](https://openaccess.thecvf.com/content/CVPR2022/papers/Hu_EfficientNeRF__Efficient_Neural_Radiance_Fields_CVPR_2022_paper.pdf)|\n|2022|CVPR||[Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fields](https://openaccess.thecvf.com/content/CVPR2022/papers/Barron_Mip-NeRF_360_Unbounded_Anti-Aliased_Neural_Radiance_Fields_CVPR_2022_paper.pdf)|\n|2021|ICCV|[TF](https://github.com/google/mipnerf)|[Mip-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)|\n|2021|ICCV|[Torch](https://github.com/sxyu/plenoctree)|[PlenOctrees for Real-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/)|\n|2021|ICCV|[Torch](https://github.com/creiser/kilonerf)|[KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs](https://openaccess.thecvf.com/content/ICCV2021/papers/Reiser_KiloNeRF_Speeding_Up_Neural_Radiance_Fields_With_Thousands_of_Tiny_ICCV_2021_paper.pdf)|\n|2021|ICCV|[TF](https://github.com/google-research/google-research/tree/master/snerg)|[Baking Neural Radiance Fields for Real-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/)|\n|2021|CVPR|[TF](https://github.com/google-research/google-research/tree/master/snerg)|[DeRF: Decomposed Radiance Fields](https://openaccess.thecvf.com/content/CVPR2021/papers/Rebain_DeRF_Decomposed_Radiance_Fields_CVPR_2021_paper.pdf)|[Project Page](https://ubc-vision.github.io/derf/)|\n\n### NeRF Related Tasks\n\n#### Deblur \u0026 Denoise\n\n|Year|Conf/Jour|Code|Title|OtherInfo|\n|:-:|:-:|:-:|:-:|:-:|\n|2022|CVPR|[Torch](https://github.com/limacv/Deblur-NeRF)|[Deblur-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)|\n|2022|CVPR||[NAN: Noise-Aware NeRFs for Burst-Denoising](https://openaccess.thecvf.com/content/CVPR2022/papers/Pearl_NAN_Noise-Aware_NeRFs_for_Burst-Denoising_CVPR_2022_paper.pdf)|[Project Page](https://noise-aware-nerf.github.io/)|\n|2022|CVPR||[NeRF in the Dark: High Dynamic Range View Synthesis from Noisy Raw Images](https://openaccess.thecvf.com/content/CVPR2022/papers/Mildenhall_NeRF_in_the_Dark_High_Dynamic_Range_View_Synthesis_From_CVPR_2022_paper.pdf)|\n\n#### Depth Estimation\n\n|Year|Conf/Jour|Code|Title|OtherInfo|\n|:-:|:-:|:-:|:-:|:-:|\n|2022|CVPR||[AR-NeRF: Unsupervised Learning of Depth and Defocus Effects from Natural Images with Aperture Rendering Neural Radiance Fields](https://openaccess.thecvf.com/content/CVPR2022/papers/Kaneko_AR-NeRF_Unsupervised_Learning_of_Depth_and_Defocus_Effects_From_Natural_CVPR_2022_paper.pdf)|[Project Page](https://www.kecl.ntt.co.jp/people/kaneko.takuhiro/projects/ar-nerf/)|\n|2021|ICCV|[Torch](https://github.com/weiyithu/NerfingMVS)|[NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-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)|\n|2021|ICCV|[Torch](https://github.com/vincentfung13/MINE)|[MINE: Towards Continuous Depth MPI with NeRF for Novel View Synthesis](https://openaccess.thecvf.com/content/ICCV2021/papers/Li_MINE_Towards_Continuous_Depth_MPI_With_NeRF_for_Novel_View_ICCV_2021_paper.pdf)|\n\n#### Editing\n\n|Year|Conf/Jour|Code|Title|OtherInfo|\n|:-:|:-:|:-:|:-:|:-:|\n|2022|NeurIPS|[Torch](https://github.com/showlab/DeVRF)|[DeVRF: Fast Deformable Voxel Radiance Fields for Dynamic Scenes](https://arxiv.org/pdf/2205.15723.pdf)|[Project Page](https://jia-wei-liu.github.io/DeVRF/)|\n|2022|NeurIPS||[Decomposing NeRF for Editing via Feature Field Distillation](https://arxiv.org/pdf/2205.15585.pdf)|[Project Page](https://pfnet-research.github.io/distilled-feature-fields/)|\n|2022|NeurIPS||[CageNeRF: Cage-based Neural Radiance Field for Generalized 3D Deformation and Animation](https://openreview.net/pdf?id=kUnHCGiILeU)||\n|2022|ECCV|[Comming Soon](https://github.com/xth430/deforming-nerf)|[Deforming Radiance Fields with Cages](https://arxiv.org/pdf/2207.12298.pdf)|[Project Page](https://xth430.github.io/deforming-nerf/)|\n|2022|ECCV|[Torch](https://github.com/zhuhao-nju/mofanerf)|[MoFaNeRF: Morphable Facial Neural Radiance Field](https://arxiv.org/pdf/2112.02308.pdf)||\n|2022|ECCV|[Torch](https://github.com/ywq/psnerf)|[PS-NeRF: Neural Inverse Rendering for Multi-view Photometric Stereo](https://ywq.github.io/psnerf/)|[Project Page](https://ywq.github.io/psnerf/)|\n|2022|ECCV|[Torch](https://github.com/zju3dv/neumesh)|[NeuMesh: Learning Disentangled Neural Mesh-based Implicit Field for Geometry and Texture Editing](https://arxiv.org/pdf/2207.11911.pdf)|[Project Page](https://zju3dv.github.io/neumesh/)|\n|2022|CVPR|[Torch](https://github.com/lwwu2/diver-rt)|[DIVeR: Real-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)|\n|2022|CVPR|[Jittor](https://github.com/IGLICT/NeRF-Editing)|[NeRF-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)|\n|2022|CVPR|[Torch](https://github.com/MrTornado24/FENeRF)|[FENeRF: Face Editing in Neural Radiance Fields](https://openaccess.thecvf.com/content/CVPR2022/papers/Sun_FENeRF_Face_Editing_in_Neural_Radiance_Fields_CVPR_2022_paper.pdf)|\n|2022|CVPR||[RigNeRF: Fully Controllable Neural 3D Portraits](https://openaccess.thecvf.com/content/CVPR2022/papers/Athar_RigNeRF_Fully_Controllable_Neural_3D_Portraits_CVPR_2022_paper.pdf)|\n|2022|CVPR||[CoNeRF: Controllable Neural Radiance Fields](https://openaccess.thecvf.com/content/CVPR2022/papers/Kania_CoNeRF_Controllable_Neural_Radiance_Fields_CVPR_2022_paper.pdf)|\n|2021|ICCV|[Torch](https://github.com/zju3dv/object_nerf)|[Learning Object-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/)|\n|2021|ICCV|[Torch](https://github.com/stevliu/editnerf)|[Editing Conditional Radiance Fields](https://openaccess.thecvf.com/content/ICCV2021/papers/Liu_Editing_Conditional_Radiance_Fields_ICCV_2021_paper.pdf)|[Project Page](http://editnerf.csail.mit.edu/)|\n|2021|CVPR|[Torch](https://github.com/autonomousvision/giraffe)|[GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields](https://openaccess.thecvf.com/content/CVPR2021/papers/Niemeyer_GIRAFFE_Representing_Scenes_As_Compositional_Generative_Neural_Feature_Fields_CVPR_2021_paper.pdf)|[Project Page](https://m-niemeyer.github.io/project-pages/giraffe/index.html)|\n|2021|CVPR|[Torch](https://github.com/microsoft/DIF-Net)|[Deformed Implicit Field: Modeling 3D Shapes with Learned Dense Correspondence](https://openaccess.thecvf.com/content/CVPR2021/papers/Deng_Deformed_Implicit_Field_Modeling_3D_Shapes_With_Learned_Dense_Correspondence_CVPR_2021_paper.pdf)||\n|2021|NeurIPS|[Torch](https://github.com/stevenygd/NFGP)|[Geometry Processing with Neural Fields](https://proceedings.neurips.cc/paper/2021/file/bd686fd640be98efaae0091fa301e613-Paper.pdf)|[Project Page](https://www.guandaoyang.com/NFGP/)|\n\n#### Face\n\n|Year|Conf/Jour|Code|Title|OtherInfo|\n|:-:|:-:|:-:|:-:|:-:|\n|2022|NeurIPS||[Generative Neural Articulated Radiance Fields](https://arxiv.org/pdf/2206.14314.pdf)||\n|2022|ECCV|[Torch](https://github.com/sstzal/DFRF)|[Learning Dynamic Facial Radiance Fields for Few-Shot Talking Head Synthesis](https://arxiv.org/pdf/2207.11770.pdf)|[Project Page](https://sstzal.github.io/DFRF/)|\n|2022|ECCV|[Torch](https://github.com/jgkwak95/SURF-GAN)|[Injecting 3D Perception of Controllable NeRF-GAN into StyleGAN for Editable Portrait Image Synthesis](https://arxiv.org/pdf/2207.10257.pdf)||\n|2022|ECCV|[Torch](https://github.com/zhuhao-nju/mofanerf)|[MoFaNeRF: Morphable Facial Neural Radiance Field](https://arxiv.org/pdf/2112.02308.pdf)||\n|2022|ECCV|[Torch](https://github.com/donydchen/sem2nerf)|[Sem2NeRF: Converting Single-View Semantic Masks to Neural Radiance Fields](https://arxiv.org/pdf/2203.10821.pdf)|[Project Page](https://donydchen.github.io/sem2nerf/)|\n|2022|CVPR||[LOLNeRF: Learn from One Look](https://openaccess.thecvf.com/content/CVPR2022/papers/Rebain_LOLNerf_Learn_From_One_Look_CVPR_2022_paper.pdf)|[Project Page](https://ubc-vision.github.io/lolnerf/)|\n|2022|CVPR|[Torch](https://github.com/MrTornado24/FENeRF)|[FENeRF: Face Editing in Neural Radiance Fields](https://openaccess.thecvf.com/content/CVPR2022/papers/Sun_FENeRF_Face_Editing_in_Neural_Radiance_Fields_CVPR_2022_paper.pdf)|\n|2022|CVPR||[CoNeRF: Controllable Neural Radiance Fields](https://openaccess.thecvf.com/content/CVPR2022/papers/Kania_CoNeRF_Controllable_Neural_Radiance_Fields_CVPR_2022_paper.pdf)|\n|2022|CVPR|[Torch](https://github.com/CrisHY1995/headnerf)|[HeadNeRF: A Real-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)|\n|2022|CVPR|[Torch](https://github.com/primecai/Pix2NeRF)|[Pix2NeRF: Unsupervised Conditional π-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)|\n|2021|ICCV|[Torch](https://github.com/YudongGuo/AD-NeRF)|[AD-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)|\n|2021|CVPR||[Dynamic Neural Radiance Fields for Monocular 4D Facial Avatar Reconstruction](https://openaccess.thecvf.com/content/CVPR2021/papers/Gafni_Dynamic_Neural_Radiance_Fields_for_Monocular_4D_Facial_Avatar_Reconstruction_CVPR_2021_paper.pdf)|[Project Page](https://gafniguy.github.io/4D-Facial-Avatars/)|\n\n#### High Dynamic Range (HDR)\n\n|Year|Conf/Jour|Code|Title|OtherInfo|\n|:-:|:-:|:-:|:-:|:-:|\n|2022|ECCV|[Comming Soon](https://github.com/postech-ami/HDR-Plenoxels)|[HDR-Plenoxels: Self-Calibrating High Dynamic Range Radiance Fields](https://arxiv.org/pdf/2208.06787.pdf)||\n|2022|CVPR||[HDR-NeRF: High Dynamic Range Neural Radiance Fields](https://openaccess.thecvf.com/content/CVPR2022/papers/Huang_HDR-NeRF_High_Dynamic_Range_Neural_Radiance_Fields_CVPR_2022_paper.pdf)|\n\n#### Human\n\n|Year|Conf/Jour|Code|Title|OtherInfo|\n|:-:|:-:|:-:|:-:|:-:|\n|2022|NeurIPS||[Generative Neural Articulated Radiance Fields](https://arxiv.org/pdf/2206.14314.pdf)||\n|2022|ECCV||[Geometry-Guided Progressive NeRF for Generalizable and Efficient Neural Human Rendering](https://arxiv.org/pdf/2112.04312.pdf)||\n|2022|ECCV|[Torch](https://github.com/facebookresearch/KeypointNeRF)|[KeypointNeRF: Generalizing Image-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/)|\n|2022|ECCV|[Torch](https://github.com/apple/ml-neuman)|[NeuMan: Neural Human Radiance Field from a Single Video](https://arxiv.org/abs/2203.12575)||\n|2022|CVPR||[Structured Local Radiance Fields for Human Avatar Modeling](https://openaccess.thecvf.com/content/CVPR2022/papers/Zheng_Structured_Local_Radiance_Fields_for_Human_Avatar_Modeling_CVPR_2022_paper.pdf)|\n|2022|CVPR|[Torch](https://github.com/pfnet-research/surface-aligned-nerf)|[Surface-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)|\n|2022|CVPR|[Torch](https://github.com/chungyiweng/humannerf)|[HumanNeRF: Free-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)|\n|2022|CVPR||[DoubleField: Bridging the Neural Surface and Radiance Fields for High-fidelity Human Reconstruction and Rendering](https://openaccess.thecvf.com/content/CVPR2022/papers/Shao_DoubleField_Bridging_the_Neural_Surface_and_Radiance_Fields_for_High-Fidelity_CVPR_2022_paper.pdf)|\n|2021|ICCV|[Torch](https://github.com/zju3dv/animatable_nerf)|[Animatable Neural Radiance Fields for Modeling Dynamic Human Bodies](https://openaccess.thecvf.com/content/ICCV2021/papers/Peng_Animatable_Neural_Radiance_Fields_for_Modeling_Dynamic_Human_Bodies_ICCV_2021_paper.pdf)|[Project Page](https://zju3dv.github.io/animatable_nerf/)|\n|2021|ICCV|[Torch](https://github.com/nogu-atsu/NARF)|[Neural Articulated Radiance Field](https://openaccess.thecvf.com/content/ICCV2021/papers/Noguchi_Neural_Articulated_Radiance_Field_ICCV_2021_paper.pdf)|\n|2021|ACM TOG||[Editable Free-Viewpoint Video using a Layered Neural Representation](https://arxiv.org/abs/2104.14786)|\n\n#### Image Generation\n\n##### Image Generation\n\n|Year|Conf/Jour|Code|Title|OtherInfo|\n|:-:|:-:|:-:|:-:|:-:|\n|2022|CVPR|[Torch](https://github.com/NVlabs/eg3d)|[Efficient Geometry-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/)|\n|2020|NeurIPS|[Torch](https://github.com/autonomousvision/graf)|[GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis](https://proceedings.neurips.cc/paper/2020/file/e92e1b476bb5262d793fd40931e0ed53-Paper.pdf)||\n\n##### Text \u0026 Image Guided Generation\n\n|Year|Conf/Jour|Code|Title|OtherInfo|\n|:-:|:-:|:-:|:-:|:-:|\n|2022|ECCV|[Torch](https://github.com/donydchen/sem2nerf)|[Sem2NeRF: Converting Single-View Semantic Masks to Neural Radiance Fields](https://arxiv.org/pdf/2203.10821.pdf)|[Project Page](https://donydchen.github.io/sem2nerf/)|\n|2022|CVPR|[Code](https://github.com/cassiePython/CLIPNeRF)|[CLIP-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)||\n\n#### Large Scale Scene\n\n|Year|Conf/Jour|Code|Title|OtherInfo|\n|:-:|:-:|:-:|:-:|:-:|\n|2022|ECCV|[Torch](https://github.com/r00tman/NeRF-OSR)|[NeRF for Outdoor Scene Relighting](https://arxiv.org/pdf/2112.05140.pdf)|[Project Page](https://4dqv.mpi-inf.mpg.de/NeRF-OSR/)|\n|2022|CVPR||[Urban Radiance Fields](https://openaccess.thecvf.com/content/CVPR2022/papers/Rematas_Urban_Radiance_Fields_CVPR_2022_paper.pdf)|\n|2022|CVPR|[Torch](https://github.com/jetd1/NeRFusion)|[NeRFusion: Fusing Radiance Fields for Large-Scale Scene Reconstruction](https://openaccess.thecvf.com/content/CVPR2022/papers/Zhang_NeRFusion_Fusing_Radiance_Fields_for_Large-Scale_Scene_Reconstruction_CVPR_2022_paper.pdf)|\n|2022|CVPR||[Mega-NeRF: Scalable Construction of Large-Scale NeRFs for Virtual Fly-Throughs](https://openaccess.thecvf.com/content/CVPR2022/papers/Turki_Mega-NERF_Scalable_Construction_of_Large-Scale_NeRFs_for_Virtual_Fly-Throughs_CVPR_2022_paper.pdf)|\n|2022|CVPR||[Block-NeRF: Scalable Large Scene Neural View Synthesis](https://openaccess.thecvf.com/content/CVPR2022/papers/Tancik_Block-NeRF_Scalable_Large_Scene_Neural_View_Synthesis_CVPR_2022_paper.pdf)|\n|2022|CVPR|[Torch](https://github.com/rover-xingyu/Ha-NeRF)|[Hallucinated Neural Radiance Fields in the Wild](https://openaccess.thecvf.com/content/CVPR2022/papers/Chen_Hallucinated_Neural_Radiance_Fields_in_the_Wild_CVPR_2022_paper.pdf)|\n|2021|ICCV|[Torch](https://github.com/apple/ml-gsn)|[Unconstrained Scene Generation with Locally Conditioned Radiance Fields](https://openaccess.thecvf.com/content/ICCV2021/papers/DeVries_Unconstrained_Scene_Generation_With_Locally_Conditioned_Radiance_Fields_ICCV_2021_paper.pdf)|[Project Page](https://apple.github.io/ml-gsn/)|\n|2021|CVPR||[NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections](https://openaccess.thecvf.com/content/CVPR2021/papers/Martin-Brualla_NeRF_in_the_Wild_Neural_Radiance_Fields_for_Unconstrained_Photo_CVPR_2021_paper.pdf)|[Project Page](https://nerf-w.github.io/)|\n\n#### Pose Misalignment\n\n|Year|Conf/Jour|Code|Title|OtherInfo|\n|:-:|:-:|:-:|:-:|:-:|\n|2021|ICCV||[BARF: Bundle-Adjusting Neural Radiance Fields](https://openaccess.thecvf.com/content/ICCV2021/papers/Lin_BARF_Bundle-Adjusting_Neural_Radiance_Fields_ICCV_2021_paper.pdf)|[Project Page](https://chenhsuanlin.bitbucket.io/bundle-adjusting-NeRF/)|\n\n#### Reinforcement Learning\n\n|Year|Conf/Jour|Code|Title|OtherInfo|\n|:-:|:-:|:-:|:-:|:-:|\n|2022|NeurIPS||[Reinforcement Learning with Neural Radiance Fields](https://arxiv.org/pdf/2206.01634.pdf)|[Project Page](https://dannydriess.github.io/nerf-rl/)|\n\n#### Relighting\n\n|Year|Conf/Jour|Code|Title|OtherInfo|\n|:-:|:-:|:-:|:-:|:-:|\n|2022|ECCV|[Torch](https://github.com/r00tman/NeRF-OSR)|[NeRF for Outdoor Scene Relighting](https://arxiv.org/pdf/2112.05140.pdf)|[Project Page](https://4dqv.mpi-inf.mpg.de/NeRF-OSR/)|\n|2022|ACM MM||[Factorized and Controllable Neural Re-Rendering of Outdoor Scene for Photo Extrapolation](https://arxiv.org/pdf/2207.06899.pdf)|[Project Page](https://zju3dv.github.io/neural_outdoor_rerender/)|\n|2021|CVPR|[TF](https://github.com/cgtuebingen/NeRD-Neural-Reflectance-Decomposition)|[NeRD: Neural Reflectance Decomposition from Image Collections](https://openaccess.thecvf.com/content/ICCV2021/papers/Boss_NeRD_Neural_Reflectance_Decomposition_From_Image_Collections_ICCV_2021_paper.pdf)|[Project Page](https://markboss.me/publication/2021-nerd/)|\n|2021|CVPR||[NeRV: Neural Reflectance and Visibility Fields for Relighting and View Synthesis](https://openaccess.thecvf.com/content/CVPR2021/papers/Srinivasan_NeRV_Neural_Reflectance_and_Visibility_Fields_for_Relighting_and_View_CVPR_2021_paper.pdf)||\n|2021|ACM TOG|[TF](https://github.com/google/nerfactor)|[NeRFactor: Neural Factorization of Shape and Reflectance Under an Unknown Illumination](https://dl.acm.org/doi/pdf/10.1145/3478513.3480496)|[Project Page](https://xiuming.info/projects/nerfactor/)|\n\n#### Segmentation\n\n|Year|Conf/Jour|Code|Title|OtherInfo|\n|:-:|:-:|:-:|:-:|:-:|\n|2022|NeurIPS||[Unsupervised Multi-View Object Segmentation Using Radiance Field Propagation](https://arxiv.org/abs/2210.00489)||\n|2022|NeurIPS|[TF](https://github.com/d2nerf/d2nerf)|[D^2NeRF: Self-Supervised Decoupling of Dynamic and Static Objects from a Monocular Video](https://arxiv.org/pdf/2205.15838.pdf)|[Project Page](https://d2nerf.github.io/)|\n|2022|NeurIPS||[Decomposing NeRF for Editing via Feature Field Distillation](https://arxiv.org/pdf/2205.15585.pdf)|[Project Page](https://pfnet-research.github.io/distilled-feature-fields/)|\n|2022|ECCV||[LaTeRF: Label and Text Driven Object Radiance Fields](https://arxiv.org/pdf/2207.01583.pdf)||\n\n#### Stylized\n\n|Year|Conf/Jour|Code|Title|OtherInfo|\n|:-:|:-:|:-:|:-:|:-:|\n|2022|ECCV|[Torch](https://github.com/Kai-46/ARF-svox2)|[ARF: Artistic Radiance fields](https://arxiv.org/pdf/2206.06360.pdf)|[Project Page](https://www.cs.cornell.edu/projects/arf/)|\n|2022|CVPR|[Jittor](https://github.com/IGLICT/StylizedNeRF)|[StylizedNeRF: Consistent 3D Scene Stylization as Stylized NeRF via 2D-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)|\n|2021|ICCV|[Torch](https://github.com/hhsinping/stylescene)|[Learning to Stylize Novel Views](https://openaccess.thecvf.com/content/ICCV2021/papers/Huang_Learning_To_Stylize_Novel_Views_ICCV_2021_paper.pdf)|[Project Page](https://hhsinping.github.io/3d_scene_stylization/)|\n\n#### Surface Reconstruction\n\n|Year|Conf/Jour|Code|Title|OtherInfo|\n|:-:|:-:|:-:|:-:|:-:|\n|2021|ICCV|[Torch](https://github.com/autonomousvision/unisurf)|[UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-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)|\n|2021|NeurIPS|[Torch](https://github.com/Totoro97/NeuS)|[NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction](https://arxiv.org/pdf/2106.10689.pdf)|[Project Page](https://lingjie0206.github.io/papers/NeuS/)|\n|2021|NeurIPS||[Volume Rendering of Neural Implicit Surfaces](https://proceedings.neurips.cc/paper/2021/file/25e2a30f44898b9f3e978b1786dcd85c-Paper.pdf)||\n\n#### Video\n\n|Year|Conf/Jour|Code|Title|OtherInfo|\n|:-:|:-:|:-:|:-:|:-:|\n|2022|NeurIPS|[Torch](https://github.com/showlab/DeVRF)|[DeVRF: Fast Deformable Voxel Radiance Fields for Dynamic Scenes](https://arxiv.org/pdf/2205.15723.pdf)|[Project Page](https://jia-wei-liu.github.io/DeVRF/)|\n|2022|ECCV|[Torch](https://github.com/apple/ml-neuman)|[NeuMan: Neural Human Radiance Field from a Single Video](https://arxiv.org/abs/2203.12575)||\n|2021|ACM TOG|[TF](https://github.com/google/hypernerf)|[HyperNeRF: A Higher-Dimensional Representation for Topologically Varying Neural Radiance Fields](https://arxiv.org/pdf/2106.13228.pdf)|[Project Page](https://hypernerf.github.io/)|\n|2021|CVPR|[Torch](https://github.com/albertpumarola/D-NeRF)|[D-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)|\n|2021|ICCV|[Torch](https://github.com/facebookresearch/nonrigid_nerf)|[Non-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)|\n|2021|CVPR||[Dynamic Neural Radiance Fields for Monocular 4D Facial Avatar Reconstruction](https://openaccess.thecvf.com/content/CVPR2021/papers/Gafni_Dynamic_Neural_Radiance_Fields_for_Monocular_4D_Facial_Avatar_Reconstruction_CVPR_2021_paper.pdf)|[Project Page](https://gafniguy.github.io/4D-Facial-Avatars/)|\n|2021|CVPR||[Learning Compositional Radiance Fields of Dynamic Human Heads](https://openaccess.thecvf.com/content/CVPR2021/papers/Wang_Learning_Compositional_Radiance_Fields_of_Dynamic_Human_Heads_CVPR_2021_paper.pdf)|[Project Page](https://ziyanw1.github.io/hybrid_nerf/)|\n|2021|CVPR||[Space-time Neural Irradiance Fields for Free-Viewpoint Video](https://openaccess.thecvf.com/content/CVPR2021/papers/Xian_Space-Time_Neural_Irradiance_Fields_for_Free-Viewpoint_Video_CVPR_2021_paper.pdf)|[Project Page](https://video-nerf.github.io/)\n\n\n#### View Synthesis Extrapolation\n\n|Year|Conf/Jour|Code|Title|OtherInfo|\n|:-:|:-:|:-:|:-:|:-:|\n|2022|CVPR||[Ray Priors through Reprojection: Improving Neural Radiance Fields for Novel View Extrapolation](https://openaccess.thecvf.com/content/CVPR2022/papers/Zhang_Ray_Priors_Through_Reprojection_Improving_Neural_Radiance_Fields_for_Novel_CVPR_2022_paper.pdf)||\n\n### Unclassified\n\n|Year|Conf/Jour|Code|Title|OtherInfo|\n|:-:|:-:|:-:|:-:|:-:|\n|2022|ECCV||[BungeeNeRF: Progressive Neural Radiance Field for Extreme Multiscale Scene Rendering](https://arxiv.org/abs/2112.05504)|\n|2022|CVPR||[Neural Volumetric Object Selection](https://openaccess.thecvf.com/content/CVPR2022/papers/Ren_Neural_Volumetric_Object_Selection_CVPR_2022_paper.pdf)|[Project Page](https://jason718.github.io/nvos/)|\n|2021|ICCV|[Torch](https://github.com/wbjang/code-nerf)|[CodeNeRF: Disentangled Neural Radiance Fields for Object Categories](https://openaccess.thecvf.com/content/ICCV2021/papers/Jang_CodeNeRF_Disentangled_Neural_Radiance_Fields_for_Object_Categories_ICCV_2021_paper.pdf)|\n|2021|ICCV|[Torch](https://github.com/POSTECH-CVLab/SCNeRF)|[Self-Calibrating Neural Radiance Fields](https://openaccess.thecvf.com/content/ICCV2021/papers/Jeong_Self-Calibrating_Neural_Radiance_Fields_ICCV_2021_paper.pdf)| \n\n## Datasets\n\n|Year|Name|Related Paper|Task|Instances|Note|\n|:-:|:-:|:-:|:-:|:-:|:-:|\n|2022|[PeRFception](https://postech-cvlab.github.io/PeRFception/)|[PeRFception: Perception using Radiance Fields](https://openreview.net/pdf?id=MzaPEKHv-0J)|2D classification, 3D classification, 3D segmentation|19k||\n|2021|[NeuS-DATA](https://drive.google.com/drive/folders/1Nlzejs4mfPuJYORLbDEUDWlc9IZIbU0C)|[NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction](https://arxiv.org/pdf/2106.10689.pdf)|Surface Reconstruction|-||\n|2020|[NeRF-DATA](https://drive.google.com/drive/folders/128yBriW1IG_3NJ5Rp7APSTZsJqdJdfc1)|[NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis](https://dl.acm.org/doi/pdf/10.1145/3503250)|View Synthesis|-|Benchmark|\n\n## Talks\n\n|Year|Theme|Speaker/Publisher|Language|\n|:-:|:-:|:-:|:-:|\n|2022|[TensoRF: Tensorial Radiance Fields](https://www.youtube.com/watch?v=ujOMgaKV3lA)|Zexiang Xu|EN|\n|2022|[ECCV2022 - Learning Dynamic Facial Radiance Fields for Few-Shot Talking Head Synthesis](https://www.youtube.com/watch?v=F6fkVNk9bBw)|Shens|EN|\n|2022|[[NeRF-OSR, ECCV 2022] NeRF for Outdoor Scene Relighting](https://www.youtube.com/watch?v=V8h77YMcxTg)|Vlad Golyanik (4DQV) |EN|\n|2022|[PS-NeRF: Neural Inverse Rendering for Multi-view Photometric Stereo (ECCV 2022)](https://www.youtube.com/watch?v=AhVbcevzCqc)|Yoo|EN|\n|2022|[[ECCV 2022] KeypointNeRF: Generalizing Image-based Volumetric Avatars](https://www.youtube.com/watch?v=RMs1S5k9vrk)|Marko Mihajlovic|EN|\n|2022|[[ECCV'22] Sem2NeRF: Converting Single-View Semantic Masks to Neural Radiance Fields](https://www.youtube.com/watch?v=cYr3Dz8N_9E)|Yuedong Chen|EN|\n|2022|[[CVPR 2022] Neural Volumetric Object Selection](https://www.youtube.com/watch?v=iAe5Wk0C_aA)|Jason Ren|EN|\n|2022|[[ACM-MM'22] Factorized and Controllable Neural Re-Rendering of Outdoor Scene for Photo Extrapolation](https://www.youtube.com/watch?v=gFwNBqNfqKQ)|Bangbang Yang|EN|\n|2021|[Geometry Processing with Neural Fields](https://www.youtube.com/watch?v=y6LKzQ6ACTw)|Guandao Yang|EN|\n|2021|[Editing Conditional Radiance Fields](https://www.youtube.com/watch?v=9qwRD4ejOpw)|Steven Liu|EN|\n|2021|[Michael Niemeyer: Generative Neural Scene Representations 3D Representation Seminar](https://www.youtube.com/watch?v=scnXyCSMJF4)|Yen-Chen Lin|EN|\n|2021|[NeRFactor: Neural Factorization of Shape and Reflectance Under an Unknown Illumination](https://www.youtube.com/watch?v=UUVSPJlwhPg)|Xiuming Zhang|EN|\n|2020|[NeRD: Neural Reflectance Decomposition from Image Collections](https://www.youtube.com/watch?v=JL-qMTXw9VU)|Mark Boss|EN|\n|2020|[NeRF: Neural Radiance Fields](https://www.youtube.com/watch?v=JuH79E8rdKc)|Matthew Tancik|EN|\n\n\u003c!-- ## Blogs\n\n|Year|Title|Writer|Language|\n|:-:|:-:|:-:|:-:|\n|2022|[NeRF及其发展](https://zhuanlan.zhihu.com/p/512538748)|yuqiSun|CN|\n|2022|[NeRF at CVPR 2022](https://dellaert.github.io/NeRF22/)|Frank Dellaert|EN|\n|2021|[NeRF at ICCV 2021](https://dellaert.github.io/NeRF21/)|Frank Dellaert|EN|\n|2020|[NeRF Explosion 2020](https://dellaert.github.io/NeRF/)|Frank Dellaert|EN| --\u003e\n\n## Acknowledgment\nWhen we reviewed the literatures about NeRF, we found that this excellent [repo](https://github.com/yenchenlin/awesome-NeRF) had not been updated for a long time, so we reorganized and released our [awesome-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.\n\n## Team\n### Team Members\n[Zhongwei Qiu](https://github.com/qiuzhongwei-USTB) (Leader), [Zijiang Yang](https://github.com/koolo233), [Tianle Cheng](https://github.com/Oak112)\n### Contributors\n\n[Hutao99999](https://github.com/Hutao99999), [Tyler Luan](https://github.com/ykk648)\n\n\n","projects_url":"https://awesome.ecosyste.ms/api/v1/lists/matrixbrain%2Fawesome-nerf/projects"}