mlsanityData to 7 Oct 2026

NeuRAD: Neural Rendering for Autonomous Driving

arXiv 2311.15260 ↗First posted 26 Nov 2023cs.CVcited by 146

On the map: End-to-end autonomous driving → End-to-end system architecture

Abstract (arXiv)

Neural radiance fields (NeRFs) have gained popularity in the autonomous driving (AD) community. Recent methods show NeRFs' potential for closed-loop simulation, enabling testing of AD systems, and as an advanced training data augmentation technique. However, existing methods often require long training times, dense semantic supervision, or lack generalizability. This, in turn, hinders the application of NeRFs for AD at scale. In this paper, we propose NeuRAD, a robust novel view synthesis method tailored to dynamic AD data. Our method features simple network design, extensive sensor modeling for both camera and lidar -- including rolling shutter, beam divergence and ray dropping -- and is applicable to multiple datasets out of the box. We verify its performance on five popular AD datasets, achieving state-of-the-art performance across the board. To encourage further development, we will openly release the NeuRAD source code. See https://github.com/georghess/NeuRAD .

Key facts. Cited by 146 papers in the map (data through 7 Oct 2026). Placed in End-to-end system architecture, one of 9 directions in End-to-end autonomous driving. Builds on 41 of its 50 references that are in the map. First posted on arXiv 26 Nov 2023.

Builds on

41 of 50 references.

References · 41

  1. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,029
  2. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,141
  3. 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,510
  4. 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,485
  5. 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,698
  6. 2017CARLA: An Open Urban Driving Simulatorcited by 2,431
  7. 2018Occupancy Networks: Learning 3D Reconstruction in Function Spacecited by 2,037
  8. 2021Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fieldscited by 2,013
  9. 2021Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fieldscited by 1,957
  10. 2021NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstructioncited by 1,701
  11. 2021Plenoxels: Radiance Fields without Neural Networkscited by 1,607
  12. 2022TensoRF: Tensorial Radiance Fieldscited by 1,275
29 more
  1. 2020NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collectionscited by 1,230
  2. 2018On the Continuity of Rotation Representations in Neural Networkscited by 1,186
  3. 2017High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANscited by 1,176
  4. 2022Block-NeRF: Scalable Large Scene Neural View Synthesiscited by 720
  5. 2023Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecastingcited by 701
  6. 2019Local Light Field Fusion: Practical View Synthesis with Prescriptive Sampling Guidelinescited by 672
  7. 2023Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance Fieldscited by 667
  8. 2021UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstructioncited by 643
  9. 2023Nerfstudio: A Modular Framework for Neural Radiance Field Developmentcited by 596
  10. 2017AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehiclescited by 517
  11. 2023Instruct-NeRF2NeRF: Editing 3D Scenes with Instructionscited by 482
  12. 2023Neuralangelo: High-Fidelity Neural Surface Reconstructioncited by 464
  13. 2022NeuS2: Fast Learning of Neural Implicit Surfaces for Multi-view Reconstructioncited by 311
  14. 2020Neural Scene Graphs for Dynamic Scenescited by 298
  15. 2023UniSim: A Neural Closed-Loop Sensor Simulatorcited by 294
  16. 2021Urban Radiance Fieldscited by 263
  17. 2022Panoptic Neural Fields: A Semantic Object-Aware Neural Scene Representationcited by 243
  18. 2021PandaSet: Advanced Sensor Suite Dataset for Autonomous Drivingcited by 186
  19. 2023MARS: An Instance-aware, Modular and Realistic Simulator for Autonomous Drivingcited by 170
  20. 2022Panoptic NeRF: 3D-to-2D Label Transfer for Panoptic Urban Scene Segmentationcited by 152
  21. 2023SUDS: Scalable Urban Dynamic Scenescited by 151
  22. 2023BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown Objectscited by 144
  23. 2023Tri-MipRF: Tri-Mip Representation for Efficient Anti-Aliasing Neural Radiance Fieldscited by 142
  24. 2023S-NeRF: Neural Radiance Fields for Street Viewscited by 116
  25. 2023NerfAcc: Efficient Sampling Accelerates NeRFscited by 90
  26. 2023Zenseact Open Dataset: A large-scale and diverse multimodal dataset for autonomous drivingcited by 83
  27. 2023Neural LiDAR Fields for Novel View Synthesiscited by 65
  28. 2021Immortal Tracker: Tracklet Never Diescited by 42
  29. 2023Reconstructing Objects in-the-wild for Realistic Sensor Simulationcited by 21

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 39; 2025: 68; 2026: 38.

146 papers.

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  1. 2024NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarkingcited by 343
  2. 2024Street Gaussians: Modeling Dynamic Urban Scenes with Gaussian Splattingcited by 218
  3. 2024OmniRe: Omni Urban Scene Reconstructioncited by 159
  4. 2025Pseudo-Simulation for Autonomous Drivingcited by 141
  5. 2024DriveDreamer4D: World Models Are Effective Data Machines for 4D Driving Scene Representationcited by 123
  6. 2024textitS3Gaussian: Self-Supervised Street Gaussians for Autonomous Drivingcited by 105
  7. 2025Hydra-MDP++: Advancing End-to-End Driving via Expert-Guided Hydra-Distillationcited by 93
  8. 2024ReconDreamer: Crafting World Models for Driving Scene Reconstruction via Online Restorationcited by 89
  9. 2024HUGSIM: A Real-Time, Photo-Realistic and Closed-Loop Simulator for Autonomous Drivingcited by 84
  10. 2025RAD: Training an End-to-End Driving Policy via Large-Scale 3DGS-based Reinforcement Learningcited by 76
  11. 2024SplatAD: Real-Time Lidar and Camera Rendering with 3D Gaussian Splatting for Autonomous Drivingcited by 66
  12. 2024NeuroNCAP: Photorealistic Closed-loop Safety Testing for Autonomous Drivingcited by 61
38 more
  1. 2024InfiniCube: Unbounded and Controllable Dynamic 3D Driving Scene Generation with World-Guided Video Modelscited by 53
  2. 2024STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenescited by 53
  3. 2024FreeVS: Generative View Synthesis on Free Driving Trajectorycited by 52
  4. 2024StreetCrafter: Street View Synthesis with Controllable Video Diffusion Modelscited by 49
  5. 2024SGD: Street View Synthesis with Gaussian Splatting and Diffusion Priorcited by 36
  6. 2025ReconDreamer++: Harmonizing Generative and Reconstructive Models for Driving Scene Representationcited by 36
  7. 2024Dynamic 3D Gaussian Fields for Urban Areascited by 35
  8. 2024FreeSim: Toward Free-viewpoint Camera Simulation in Driving Scenescited by 30
  9. 2023Towards Knowledge-driven Autonomous Drivingcited by 29
  10. 2024G3R: Gradient Guided Generalizable Reconstructioncited by 29
  11. 2024S-NeRF++: Autonomous Driving Simulation via Neural Reconstruction and Generationcited by 28
  12. 2025Scenario Dreamer: Vectorized Latent Diffusion for Generating Driving Simulation Environmentscited by 27
  13. 2025CoDa-4DGS: Dynamic Gaussian Splatting with Context and Deformation Awareness for Autonomous Drivingcited by 25
  14. 2024PreSight: Enhancing Autonomous Vehicle Perception with City-Scale NeRF Priorscited by 21
  15. 2024Are NeRFs ready for autonomous driving? Towards closing the real-to-simulation gapcited by 20
  16. 2024SplatFlow: Self-Supervised Dynamic Gaussian Splatting in Neural Motion Flow Field for Autonomous Drivingcited by 20
  17. 2024Neural Radiance Field in Autonomous Driving: A Surveycited by 19
  18. 2025Viser: Imperative, Web-based 3D Visualization in Pythoncited by 19
  19. 2024PixelGaussian: Generalizable 3D Gaussian Reconstruction from Arbitrary Viewscited by 18
  20. 2025MTGS: Multi-Traversal Gaussian Splattingcited by 17
  21. 2025R3D2: Realistic 3D Asset Insertion via Diffusion for Autonomous Driving Simulationcited by 17
  22. 2025AD-GS: Object-Aware B-Spline Gaussian Splatting for Self-Supervised Autonomous Drivingcited by 17
  23. 2025PRIX: Learning to Plan from Raw Pixels for End-to-End Autonomous Drivingcited by 16
  24. 2024DeSplat: Decomposed Gaussian Splatting for Distractor-Free Renderingcited by 15
  25. 2025RadarSplat: Radar Gaussian Splatting for High-Fidelity Data Synthesis and 3D Reconstruction of Autonomous Driving Scenescited by 15
  26. 2024RoDUS: Robust Decomposition of Static and Dynamic Elements in Urban Scenescited by 14
  27. 2025Unifying Appearance Codes and Bilateral Grids for Driving Scene Gaussian Splattingcited by 14
  28. 2024EMD: Explicit Motion Modeling for High-Quality Street Gaussian Splattingcited by 13
  29. 2024Extrapolated Urban View Synthesis Benchmarkcited by 13
  30. 2025Decoupled Diffusion Sparks Adaptive Scene Generationcited by 12
  31. 2025CRUISE: Cooperative Reconstruction and Editing in V2X Scenarios using Gaussian Splattingcited by 11
  32. 2025GS-Occ3D: Scaling Vision-only Occupancy Reconstruction with Gaussian Splattingcited by 11
  33. 2024LiDAR-RT: Gaussian-based Ray Tracing for Dynamic LiDAR Re-simulationcited by 10
  34. 2025Learning-based 3D Reconstruction in Autonomous Driving: A Comprehensive Surveycited by 9
  35. 2024Recurrent Aligned Network for Generalized Pedestrian Trajectory Predictioncited by 8
  36. 2024Memorize What Matters: Emergent Scene Decomposition from Multitraversecited by 8
  37. 2024UniCal: Unified Neural Sensor Calibrationcited by 8
  38. 2024LiHi-GS: LiDAR-Supervised Gaussian Splatting for Highway Driving Scene Reconstructioncited by 8

50 most cited of 146 All 146 (JSON)

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  1. 2024Learning autonomous driving from aerial imagery
  2. 2024XLD: A Cross-Lane Dataset for Benchmarking Novel Driving View Synthesis
  3. 2025Uni-Gaussians: Unifying Camera and Lidar Simulation with Gaussians for Dynamic Driving Scenarios
  4. 2024ID-NeRF: Indirect Diffusion-guided Neural Radiance Fields for Generalizable View Synthesis
  5. 2025SynAD: Enhancing Real-World End-to-End Autonomous Driving Models through Synthetic Data Integration
  6. 2023Generating Transferable Adversarial Simulation Scenarios for Self-Driving via Neural Rendering
  7. 2025Glad: A Streaming Scene Generator for Autonomous Driving
  8. 2026RS2AD-LiDAR: End-to-End Autonomous Driving LiDAR Data Generation from Roadside Sensor Observations