We try to collect all interesting neural based rendering projcets in this repository to get a full-view of the emerging technology. Please submit pull request if you think something is not correct or you have more to share with everyone. Collective video and information about this area has been published in my Bilibili space: https://space.bilibili.com/455056488. You can follow it up if you want.
Thank you in advance for upcoming contributions!
Neural rendering is a new and rapidly emerging field that combines generative machine learning techniques with physical knowledge from computer graphics, e.g., by the integration of differentiable rendering into network training.
| Paper | Conf | Author | Code | Category |
|---|---|---|---|---|
| PaletteNeRF: Palette-based Appearance Editing of Neural Radiance Fields | Unknown | Zhangfei Kuang，Fujun Luan, Zhixin Shu, Gordon Wetzstein, Kalyan Sunkavalli | Editing | |
| Panoptic Lifting for 3D Scene Understanding with Neural Fields | Unknown | Yawar Siddiqui, Lorenzo Porzi, Samuel Rota Bulò, Norman Müller, Matthias Nießner, Angela Dai, Peter Kontschieder | Segmentation | |
| Rodin: A Generative Model for Sculpting 3D Digital Avatars Using Diffusion | Unknown | Tengfei Wang, Bo Zhang, Ting Zhang, Shuyang Gu, Jianmin Bao, Tadas Baltrusaitis, Jingjing Shen, Dong Chen, Fang Wen, Qifeng Chen, Baining Guo | Modeling & Rendering | |
| Real-Time Neural Light Field on Mobile Devices | Unknown | Junli Cao, Huan Wang, Pavlo Chemerys, Vladislav Shakhrai, Ju Hu, Yun Fu, Denys Makoviichuk, Sergey Tulyakov, Jian Ren | Github Homepage | Modeling & Rendering |
| NeRF-Art: Text-Driven Neural Radiance Fields Stylization | Unknown | Can Wang, Ruixiang Jiang, Menglei Chai, Mingming He, Dongdong Chen, Jing Liao | Github Homepage | Stylization |
| 4K-NeRF: High Fidelity Neural Radiance Fields at Ultra High Resolutions | Unknown | Zhongshu Wang, Lingzhi Li, Zhen Shen, Li Shen, Liefeng Bo | Github Homepage | Modeling & Rendering |
| READ: Large-Scale Neural Scene Rendering for Autonomous Driving | Unknown | Siddhant Ranade, Christoph Lassner, Kai Li, Christian Haene, Shen-Chi Chen, Jean-Charles Bazin, Sofien Bouaziz | Github Homepage | Modeling & Rendering |
| SSDNeRF: Semantic Soft Decomposition of Neural Radiance Fields | Unknown | Siddhant Ranade, Christoph Lassner, Kai Li, Christian Haene, Shen-Chi Chen, Jean-Charles Bazin, Sofien Bouaziz | Modeling & Rendering | |
| DiffRF: Rendering-guided 3D Radiance Field Diffusion | Unknown | Norman Müller, Yawar Siddiqui, Lorenzo Porzi, Samuel Rota Bulò, Peter Kontschieder, Matthias Nießner | Modeling & Rendering | |
| CageNeRF: Cage-based Neural Radiance Fields for Genrenlized 3D Deformation and Animation | NeurIPS 2022 | Yicong Peng, Yichao Yan, Shenqi Liu, Yuhao Cheng, Shanyan Guan, Bowen Pan, Guangtao Zhai, Xiaokang Yang | Github Homepage | Animation |
| Deforming Radiance Fields with Cages | ECCV 2022 | Tianhan Wu, Tatsuya | Github Homepage | Animation |
| Reinforcement Learning with Neural Radiance Fields | NeurIPS 2022 | Yicong Peng, Yichao Yan, Shenqi Liu, Yuhao Cheng, Shanyan Guan, Bowen Pan, Guangtao Zhai, Xiaokang Yang | Reinforcement Learning | |
| Learning Dynamic Facial Radiance Fields for Few-Shot Talking Head Synthesis | ECCV 2022 | Shuai Shen, Wanhua Li, Zheng Zhu, Yueqi Duan, Jie Zhou, Jiwen Lu | Github Homepage | Talking Head |
| LaTeRF: Label and Text Driven Radiance Fields | ECCV 2022 | Ashkan Mirzaei, Yash Kant, Jonathan Kelly, Igor Gilitschenski | Github Homepage | Modeling & Rendering |
| PS-NeRF: Nerual Inverse Rendering for Multi-View Photometric Stereo | ECCV 2022 | Wenqi Yang, Chaofeng Chen, Zhenfang Chen, Kwan-Yee K. Wong | Github Homepage | Modeling & Rendering |
| MoFaNeRF: Morphable Facial Neural Radiance Field | ECCV 2022 | Yiyu Zhuang, Hao Zhu, Xusen Sun, Xun Cao | Github Homepage | Modeling & Rendering |
| Conditional-Flow NeRF: Accurate 3D Modelling with Reliable Uncertaining Quantification | ECCV 2022 | Jianxiong Shen, Antonio Agudo, Francesc Moreno-Noguer, Adria Ruiz | Github Homepage | Modeling & Rendering |
| Sem2NeRF: Converting Single-View Semantic Masks To Neural Radiance Fields | ECCV 2022 | Yuedong Chen, Qianyi Wu, Chuanxia Zheng, Tat-Jen Cham, Jianfei Cai | Github Homepage | Modeling & Rendering |
| KeypointNeRF: Generalizating Image-Based Volumetric Avatars Using Relative Spatial Encoding of Keypoints | ECCV 2022 | Marko Mihajlovic, Aayush Bansal, Michael Zollhöfer, Siyu Tang, Shunsuke Saito | Github Homepage | Modeling & Rendering |
| NeRF for Outdoor Scene Relighting | ECCV 2022 | Viktor Rudnev, Mohamed Elgharib, William Smith, Lingjie Liu, Vladislav Golyanik, Christian Theobalt | Github Homepage | Modeling & Rendering |
| Injecting 3D Perception of Controllable NeRF-GAN into StyleGAN for Editable Portrait Image Synthesis | ECCV 2022 | Jeong-gi Kwak, Yuanming Li, Dongsik Yoon, Donghyeon Kim, David Han, Hanseok Ko | Github Homepage | Modeling & Rendering |
| AdaNeRF: Adaptive Sampling for Real-Time Rendering of Neural Radiance Fields | ECCV 2022 | Andreas Kurz, Thomas Neff, Zhaoyang Lv, Michael Zollhöfer, Markus Steinberger | Github Homepage | Modeling & Rendering |
| GeoAug: Data Augmentation for Few-Shot NeRF with Geometry Constraints | ECCV 2022 | Di Chen, Yu Liu, Lianghua Huang, Bin Wang, Pan Pan | Modeling & Rendering | |
| SinNeRF: Trainin Neural Radiance Fields on Complex Scenes from a Single Image | ECCV 2022 | Dejia Xu, Yifan Jiang, Peihao Wang, Zhiwen Fan, Humphrey Shi, Zhangyang Wang | Github Homepage | Modeling & Rendering |
| Geometry-Guided Progressive NeRF for Generalizble and Efficient Neural Human Rendering | ECCV 2022 | Mingfei Chen, Jianfeng Zhang, Xiangyu Xu, Lijuan Liu, Yujun Cai, Jiashi Feng, Shuicheng Yan | Github Homepage | Modeling & Rendering |
| Neural-Sim: Learning to Generate Training Data with NeRF | ECCV 2022 | Yunhao Ge, Harkirat Behl, Jiashu Xu, Suriya Gunasekar, Neel Joshi, Yale Song, Xin Wang, Laurent Itti, Vibhav Vineet | Github Homepage | |
| BungeeNeRF: Progressive Neural Radiance Field for Extreme Multi-Scale Scene Rendering | ECCV 2022 | Yuanbo Xiangli, Linning Xu, Xingang Pan, Nanxuan Zhao, Anyi Rao, Christian Theobalt, Bo Dai, Dahua Lin | Github Homepage | Modeling & Rendering |
| ActiveNeRF: Learning Where to See with Uncertainty Estimation | ECCV 2022 | Xuran Pan, Zihang Lai, Shiji Song, Gao Huang | Github Homepage | |
| Paper | Conf | Author | Code | Area |
|---|---|---|---|---|
| ViewFormer: NeRF-Free Neural Rendering from Few Images Using Transformers | ECCV 2022 | Jonáš Kulhánek, Erik Derner, Torsten Sattler, Robert Babuška | Github Homepage | Rendering |
| Project name | Github homepage | Project Description |
|---|---|---|
| nerfstudio | Homepage | Nerfstudio provides a simple API that allows for a simplified end-to-end process of creating, training, and testing NeRFs. The library supports a more interpretable implementation of NeRFs by modularizing each component. With more modular NeRFs, we hope to create a more user-friendly experience in exploring the technology. Nerfstudio is a contributor-friendly repo with the goal of building a community where users can more easily build upon each other's contributions. |
| sdfstudio | Homepage | SDFStudio is a unified and modular framework for neural implicit surface reconstruction, built on top of the awesome nerfstudio project. We provide a unified implementation of three major implicit surface reconstruction methods: UniSurf, VolSDF, and NeuS. SDFStudio also supports various scene representions, such as MLPs, Tri-plane, and Multi-res. feature grids, and multiple point sampling strategies such as surface-guided sampling as in UniSurf, and Voxel-surface guided sampling from NeuralReconW. It further integrates recent advances in the area such as the utillization of monocular cues (MonoSDF), geometry regularization (UniSurf) and multi-view consistency (Geo-NeuS). Thanks to the unified and modular implementation, SDFStudio makes it easy to transfer ideas from one method to another. For example, Mono-NeuS applies the idea from MonoSDF to NeuS, and Geo-VolSDF applies the idea from Geo-NeuS to VolSDF. |