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awesome-of-neural-rendering
A curated list of neural rendering resources.
https://github.com/zzw-zwzhang/awesome-of-neural-rendering
Last synced: 4 days ago
JSON representation
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Table of Contents
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2021
- IBRNet: Learning Multi-View Image-Based Rendering
- GIRAFFE: Representing Scenes asCompositional Generative Neural Feature Fields - BestPaper | `Other` | [PyTorch(Author)](https://github.com/autonomousvision/giraffe) | `609` |
- Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields - Oral | `Other` | [PyTorch(Author)]() | `` |
- Self-Calibrating Neural Radiance Fields - CVLab/SCNeRF) | `72` |
- Image GANs meet Differentiable Rendering for Inverse Graphics and Interpretable 3D Neural Rendering - Oral | `Other` | [PyTorch(Author)]() | `` |
- Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields - Oral | `Other` | [PyTorch(Author)]() | `` |
- GRF: Learning a General Radiance Field for 3D Scene Representation and Rendering
- PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Material Editing and Relighting - 46/PhySG) | `33` |
- IBRNet: Learning Multi-View Image-Based Rendering
- NeX: Real-time View Synthesis with Neural Basis Expansion - Oral | `View` | [PyTorch(Author)](https://github.com/nex-mpi/nex-code/) | `320` |
- Neural Lumigraph Rendering
- AutoInt: Automatic Integration for Fast Neural Volume Rendering
- pixelNeRF: Neural Radiance Fields from One or Few Images - nerf) | `456` |
- StereoRadiance Fields (SRF): Learning View Synthesis for Sparse Views of Novel Scenes
- D-NeRF: Neural Radiance Fields for Dynamic Scenes - NeRF) | `61` |
- NeRV: Neural Reflectance and Visibility Fields for Relighting and View Synthesis
- GIRAFFE: Representing Scenes asCompositional Generative Neural Feature Fields - BestPaper | `Other` | [PyTorch(Author)](https://github.com/autonomousvision/giraffe) | `609` |
- Self-Calibrating Neural Radiance Fields - CVLab/SCNeRF) | `72` |
- Image GANs meet Differentiable Rendering for Inverse Graphics and Interpretable 3D Neural Rendering - Oral | `Other` | [PyTorch(Author)]() | `` |
- Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields - Oral | `Other` | [PyTorch(Author)]() | `` |
- GRF: Learning a General Radiance Field for 3D Scene Representation and Rendering
- PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Material Editing and Relighting - 46/PhySG) | `33` |
- IBRNet: Learning Multi-View Image-Based Rendering
- NeX: Real-time View Synthesis with Neural Basis Expansion - Oral | `View` | [PyTorch(Author)](https://github.com/nex-mpi/nex-code/) | `320` |
- Neural Lumigraph Rendering
- AutoInt: Automatic Integration for Fast Neural Volume Rendering - imaging/automatic-integration) | `80` |
- D-NeRF: Neural Radiance Fields for Dynamic Scenes - NeRF) | `61` |
- NeRV: Neural Reflectance and Visibility Fields for Relighting and View Synthesis
- GIRAFFE: Representing Scenes asCompositional Generative Neural Feature Fields - BestPaper | `Other` | [PyTorch(Author)](https://github.com/autonomousvision/giraffe) | `609` |
- NeRFactor: Neural Factorization of Shape and Reflectance Under an Unknown Illumination
- Self-Calibrating Neural Radiance Fields - CVLab/SCNeRF) | `72` |
- Image GANs meet Differentiable Rendering for Inverse Graphics and Interpretable 3D Neural Rendering - Oral | `Other` | [PyTorch(Author)]() | `` |
- PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Material Editing and Relighting - 46/PhySG) | `33` |
- NeX: Real-time View Synthesis with Neural Basis Expansion - Oral | `View` | [PyTorch(Author)](https://github.com/nex-mpi/nex-code/) | `320` |
- AutoInt: Automatic Integration for Fast Neural Volume Rendering
- pixelNeRF: Neural Radiance Fields from One or Few Images - nerf) | `456` |
- StereoRadiance Fields (SRF): Learning View Synthesis for Sparse Views of Novel Scenes
- D-NeRF: Neural Radiance Fields for Dynamic Scenes - NeRF) | `61` |
- NeRV: Neural Reflectance and Visibility Fields for Relighting and View Synthesis
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Arxiv
- NeRFactor: Neural Factorization of Shape and Reflectance Under an Unknown Illumination
- NeRFactor: Neural Factorization of Shape and Reflectance Under an Unknown Illumination
- NeuLF: Efficient Novel View Synthesis with Neural 4D Light Field - | |
- KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs
- NeuLF: Efficient Novel View Synthesis with Neural 4D Light Field - | |
- KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs
- Neural Rays for Occlusion-aware Image-based Rendering - pal/NeuRay) | `13` |
- Fast and Explicit Neural View Synthesis - | |
- HyperNeRF: A Higher-Dimensional Representation for Topologically Varying Neural Radiance Fields
- Volume Rendering of Neural Implicit Surfaces - | |
- Learning to Stylize Novel Views - | |
- Neural Ray-Tracing: Learning Surfaces and Reflectance for Relighting and View Synthesis - computational-imaging/neural_raytracing) | `7` |
- FiG-NeRF: Figure-Ground Neural Radiance Fields for 3D Object CategoryModelling
- Decomposing 3D Scenes into Objects via Unsupervised Volume Segmentation
- Inverting Neural Radiance Fields for Pose Estimation - | |
- Neural Rays for Occlusion-aware Image-based Rendering - pal/NeuRay) | `13` |
- Fast and Explicit Neural View Synthesis - | |
- HyperNeRF: A Higher-Dimensional Representation for Topologically Varying Neural Radiance Fields
- Volume Rendering of Neural Implicit Surfaces - | |
- Learning to Stylize Novel Views - | |
- Neural Ray-Tracing: Learning Surfaces and Reflectance for Relighting and View Synthesis - computational-imaging/neural_raytracing) | `7` |
- FiG-NeRF: Figure-Ground Neural Radiance Fields for 3D Object CategoryModelling
- Decomposing 3D Scenes into Objects via Unsupervised Volume Segmentation
- Inverting Neural Radiance Fields for Pose Estimation - | |
- NeuLF: Efficient Novel View Synthesis with Neural 4D Light Field - | |
- KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs
- Neural Rays for Occlusion-aware Image-based Rendering - pal/NeuRay) | `13` |
- FiG-NeRF: Figure-Ground Neural Radiance Fields for 3D Object CategoryModelling
- Decomposing 3D Scenes into Objects via Unsupervised Volume Segmentation
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2019
- Geometry-Aware Neural Rendering
- Local Light Field Fusion: Practical View Synthesis with Prescriptive Sampling Guidelines
- Deferred Neural Rendering: Image Synthesis using Neural Textures
- Scene Representation Networks: Continuous3D-Structure-Aware Neural Scene Representations - Oral | `Other` | [PyTorch(Author)](https://github.com/vsitzmann/scene-representation-networks) | `287` |
- Monocular Neural Image Based Rendering with Continuous View Control - ethz/continuous_view_synthesis) | `43` |
- Local Light Field Fusion: Practical View Synthesis with Prescriptive Sampling Guidelines
- Deferred Neural Rendering: Image Synthesis using Neural Textures
- Geometry-Aware Neural Rendering
- Scene Representation Networks: Continuous3D-Structure-Aware Neural Scene Representations - Oral | `Other` | [PyTorch(Author)](https://github.com/vsitzmann/scene-representation-networks) | `287` |
- Monocular Neural Image Based Rendering with Continuous View Control - ethz/continuous_view_synthesis) | `43` |
- Local Light Field Fusion: Practical View Synthesis with Prescriptive Sampling Guidelines
- Geometry-Aware Neural Rendering
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2020
- Multiview Neural Surface Reconstruction with Implicit Lighting and Material
- GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis
- Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision
- NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis - Oral | `View` | [TensorFlow(Author)](https://github.com/bmild/nerf) [PyTorch(3rd)](https://github.com/yenchenlin/nerf-pytorch) [PyTorch(3rd)](https://github.com/krrish94/nerf-pytorch) [Jax(3rd)](https://github.com/google-research/google-research/tree/master/jaxnerf) | `3.6k/1.1k/429/19.2k` |
- Multiview Neural Surface Reconstruction with Implicit Lighting and Material
- GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis
- Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision
- NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis - Oral | `View` | [TensorFlow(Author)](https://github.com/bmild/nerf) [PyTorch(3rd)](https://github.com/yenchenlin/nerf-pytorch) [PyTorch(3rd)](https://github.com/krrish94/nerf-pytorch) [Jax(3rd)](https://github.com/google-research/google-research/tree/master/jaxnerf) | `3.6k/1.1k/429/19.2k` |
- GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis
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Previous Venues
- Ray-casting Point-in-polyhedron Test - CESCG | `Other` | - | |
- Ray-casting Point-in-polyhedron Test - CESCG | `Other` | - | |
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Awesome Surveys
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Arxiv
- Differentiable Rendering: A Survey
- State of the Art on Neural Rendering
- awesome-neural-rendering
- awesome-neural-rendering
- New-View-Synthesis
- Differentiable Rendering: A Survey
- State of the Art on Neural Rendering
- Neural Volumetric Rendering: NeRF, etc.
- awesome-neural-rendering
- awesome-neural-rendering
- New-View-Synthesis
- State of the Art on Neural Rendering
- Neural Volumetric Rendering
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Awesome Blogs
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Videos
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Arxiv
- Matthias Niessner - Why Neural Rendering is Super Cool!
- Jon Barron - Understanding and Extending Neural Radiance Fields
- Matthew Tancik: Neural Radiance Fields for View Synthesis
- Neural Rendering (CVPR 2020)
- TUM AI Lecture Series - New Methods for Reconstruction and Neural Rendering (Christian Theobalt)
- Jon Barron - Understanding and Extending Neural Radiance Fields
- Matthew Tancik: Neural Radiance Fields for View Synthesis
- Neural Rendering (CVPR 2020)
- TUM AI Lecture Series - New Methods for Reconstruction and Neural Rendering (Christian Theobalt)
- Matthias Niessner - Why Neural Rendering is Super Cool!
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Datasets
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Arxiv
- DeepVoxels - xw83SP-0t548v63mPH), [other](https://drive.google.com/file/d/1lUvJWB6oFtT8EQ_NzBrXnmi25BufxRfl/view)
- SLF
- NeRF
- RealEstate10K
- Spaces
- LLFF
- DeepVoxels - xw83SP-0t548v63mPH), [other](https://drive.google.com/file/d/1lUvJWB6oFtT8EQ_NzBrXnmi25BufxRfl/view)
- SLF
- NeRF
- Google Scanned Objects - rmZjbapLAtdrKwg3AV-NJe)
- RealEstate10K
- Spaces
- LLFF
- NLR
- pixelNeRF
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Programming Languages
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