Merge pull request awesome-NeRF#148 from HaoyiZhu/main

add X-NERF (WACV2023) and pre-training papers
EtaCassiopeia · Feb 23, 2024 · dff4e7c · dff4e7c
2 parents 26e28f4 + 99e9b00
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diff --git a/README.md b/README.md
@@ -139,6 +139,7 @@ A curated list of awesome neural radiance fields papers, inspired by [awesome-co
 - [Rodin: A Generative Model for Sculpting 3D Digital Avatars Using Diffusion](https://3d-avatar-diffusion.microsoft.com/), Wang et al., CVPR 2023 | [github](https://3d-avatar-diffusion.microsoft.com/) | [bibtex](./citations/rodin.txt)
 - [SurfelNeRF: Neural Surfel Radiance Fields for Online Photorealistic Reconstruction of Indoor Scenes](https://arxiv.org/abs/2304.08971), Gao et al., CVPR 2023 | [github](https://gymat.github.io/SurfelNeRF-web/) | [bibtex](./citations/SurfelNeRF.txt)
 - [NeO 360: Neural Fields for Sparse View Synthesis of Outdoor Scenes](https://arxiv.org/abs/2308.12967), Irshad et al., ICCV 2023 | [github](https://github.com/zubair-irshad/NeO-360) | [bibtex](./citations/SurfelNeRF.txt)
+- [X-NeRF: Explicit Neural Radiance Field for Multi-Scene 360° Insufficient RGB-D Views](https://arxiv.org/abs/2210.05135), Zhu et al., WACV 2023 | [github](https://github.com/HaoyiZhu/XNeRF) | [bibtex](./citations/x-nerf.txt)
 </details>
 
 <details open>
@@ -258,6 +259,14 @@ A curated list of awesome neural radiance fields papers, inspired by [awesome-co
 - [Block-NeRF: Scalable Large Scene Neural View Synthesis](https://waymo.com/research/block-nerf/), Tancik et al., Arxiv 2022 | [bibtex](./citations/Block-NeRF.txt)
 </details>
 
+<details open>
+<summary>Pre-training</summary>
+
+- [Ponder: Point Cloud Pre-training via Neural Rendering](https://openaccess.thecvf.com/content/ICCV2023/html/Huang_Ponder_Point_Cloud_Pre-training_via_Neural_Rendering_ICCV_2023_paper.html), Huang et al., ICCV 2023 | [bibtex](./citations/ponder.txt)
+- [PonderV2: Pave the Way for 3D Foundation Model with A Universal Pre-training Paradigm](https://arxiv.org/abs/2310.08586), Zhu et al., Arxiv 2023 | [github](https://github.com/OpenGVLab/PonderV2) | [bibtex](./citations/ponderv2.txt)
+- [UniPAD: A Universal Pre-training Paradigm for Autonomous Driving](https://arxiv.org/abs/2310.08370), Yang et al., Arxiv 2023 | [github](https://github.com/Nightmare-n/UniPAD) | [bibtex](./citations/unipad.txt)
+</details>
+
 ## Talks
 - [NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis](https://www.youtube.com/watch?v=LCTYRqW-ne8&t=10190s), Ben Mildenhall
 - [Understanding and Extending Neural Radiance Fields](https://www.youtube.com/watch?v=nRyOzHpcr4Q&feature=emb_logo&ab_channel=cvprtum), Barron et al.

diff --git a/citations/ponder.txt b/citations/ponder.txt
@@ -0,0 +1,7 @@
+@inproceedings{huang2023ponder,
+  title={Ponder: Point cloud pre-training via neural rendering},
+  author={Huang, Di and Peng, Sida and He, Tong and Yang, Honghui and Zhou, Xiaowei and Ouyang, Wanli},
+  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
+  pages={16089--16098},
+  year={2023}
+}
diff --git a/citations/ponderv2.txt b/citations/ponderv2.txt
@@ -0,0 +1,6 @@
+@article{zhu2023ponderv2,
+  title={Ponderv2: Pave the way for 3d foundation model with a universal pre-training paradigm},
+  author={Zhu, Haoyi and Yang, Honghui and Wu, Xiaoyang and Huang, Di and Zhang, Sha and He, Xianglong and He, Tong and Zhao, Hengshuang and Shen, Chunhua and Qiao, Yu and others},
+  journal={arXiv preprint arXiv:2310.08586},
+  year={2023}
+}
diff --git a/citations/unipad.txt b/citations/unipad.txt
@@ -0,0 +1,6 @@
+@article{yang2023unipad,
+  title={Unipad: A universal pre-training paradigm for autonomous driving},
+  author={Yang, Honghui and Zhang, Sha and Huang, Di and Wu, Xiaoyang and Zhu, Haoyi and He, Tong and Tang, Shixiang and Zhao, Hengshuang and Qiu, Qibo and Lin, Binbin and others},
+  journal={arXiv preprint arXiv:2310.08370},
+  year={2023}
+}
diff --git a/citations/x-nerf.txt b/citations/x-nerf.txt
@@ -0,0 +1,7 @@
+@inproceedings{zhu2023xnerf,
+  title={X-NeRF: Explicit Neural Radiance Field for Multi-Scene 360deg Insufficient RGB-D Views},
+  author={Zhu, Haoyi},
+  booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},
+  pages={5766--5775},
+  year={2023}
+}