| Title | Plenoxels: Radiance Fields without Neural Networks |
|---|---|
| Author | Sara Fridovich-Keil and Alex Yu and Matthew Tancik and Qinhong Chen and Benjamin Recht and Angjoo Kanazawa |
| Conf/Jour | CVPR |
| Year | 2022 |
| Project | sxyu/svox2: Plenoxels: Radiance Fields without Neural Networks (github.com) |
| Paper | Plenoxels: Radiance Fields without Neural Networks (readpaper.com) |
| Title | Adaptive Shells for Efficient Neural Radiance Field Rendering |
|---|---|
| Author | Zian Wang and Tianchang Shen and Merlin Nimier-David and Nicholas Sharp and Jun Gao and Alexander Keller and Sanja Fidler and Thomas M\”uller and Zan Gojcic |
| Conf/Jour | ACM Trans. On Graph. (SIGGRAPH Asia 2023) |
| Year | 2023 |
| Project | Adaptive Shells for Efficient Neural Radiance Field Rendering (nvidia.com) |
| Paper | Adaptive Shells for Efficient Neural Radiance Field Rendering (readpaper.com) |
| Title | DMV3D: Denoising Multi-View Diffusion using 3D Large Reconstruction Model |
|---|---|
| Author | Xu, Yinghao and Tan, Hao and Luan, Fujun and Bi, Sai and Wang Peng and Li, Jihao and Shi, Zifan and Sunkavalli, Kaylan and Wetzstein Gordon and Xu, Zexiang and Zhang Kai} |
| Conf/Jour | arxiv |
| Year | 2023 |
| Project | DMV3D: Denoising Multi-View Diffusion Using 3D Large Reconstruction Mode (justimyhxu.github.io) |
| Paper | DMV3D: DENOISING MULTI-VIEW DIFFUSION USING 3D LARGE RECONSTRUCTION MODEL (readpaper.com) |
需要相机位姿 + 多视图 + Diffusion Model + NeRF Triplane2MLP
不足：
| Title | RayDF: Neural Ray-surface Distance Fields with Multi-view Consistency |
|---|---|
| Author | Zhuoman Liu, Bo Yang |
| Conf/Jour | NeurIPS |
| Year | 2023 |
| Project | RayDF: Neural Ray-surface Distance Fields with Multi-view Consistency (vlar-group.github.io) |
| Paper | RayDF: Neural Ray-surface Distance Fields with Multi-view Consistency (readpaper.com) |
| Title | DiffuStereo: High Quality Human Reconstruction via Diffusion-based Stereo Using Sparse Cameras |
|---|---|
| Author | Ruizhi Shao, Zerong Zheng, Hongwen Zhang, Jingxiang Sun, Yebin Liu |
| Conf/Jour | ECCV 2022 Oral |
| Year | 2022 |
| Project | DiffuStereo Project Page (liuyebin.com) |
| Paper | DiffuStereo: High Quality Human Reconstruction via Diffusion-based Stereo Using Sparse Cameras (readpaper.com) |
THUman2.0数据集demo结果好(除手、脸和脚)，训练代码还未开源
| Title | DoubleField: Bridging the Neural Surface and Radiance Fields for High-fidelity Human Rendering |
|---|---|
| Author | Ruizhi Shao1, Hongwen Zhang1, He Zhang2, Yanpei Cao3, Tao Yu1, and Yebin Liu1 |
| Conf/Jour | CVPR |
| Year | 2022 |
| Project | DoubleField Project Page (liuyebin.com) |
| Paper | DoubleField: Bridging the Neural Surface and Radiance Fields for High-fidelity Human Rendering. (readpaper.com) |
| Title | Human as Points: Explicit Point-based 3D Human Reconstruction from Single-view RGB Images |
|---|---|
| Author | Yingzhi Tang, Qijian Zhang, Junhui Hou, and Yebin Liu |
| Conf/Jour | arXiv |
| Year | 2023 |
| Project | yztang4/HaP (github.com) |
| Paper | Human as Points—— Explicit Point-based 3D Human Reconstruction from Single-view RGB Images.pdf (readpaper.com) |
深度估计+SMPL 估计+Diffusion Model 精细化(PointNet++)
缺陷：依赖于深度估计方法和 SMPL 估计方法的精度
为了保护隐私不对人脸进行重建
| Title | CCD-3DR: Consistent Conditioning in Diffusion for Single-Image 3D Reconstruction |
|---|---|
| Author | Yan Di1, Chenyangguang Zhang2, Pengyuan Wang1, Guangyao Zhai1, Ruida Zhang2, Fabian Manhardt3, Benjamin Busam1, Xiangyang Ji2, and Federico Tombari1,3 |
| Conf/Jour | arXiv |
| Year | 2023 |
| Project | |
| Paper | CCD-3DR: Consistent Conditioning in Diffusion for Single-Image 3D Reconstruction (readpaper.com) |
No Code
| Title | Deep Marching Tetrahedra: a Hybrid Representation for High-Resolution 3D Shape Synthesis |
|---|---|
| Author | Tianchang Shen and Jun Gao and Kangxue Yin and Ming-Yu Liu and Sanja Fidler |
| Conf/Jour | NeurIPS |
| Year | 2021 |
| Project | Deep Marching Tetrahedra: a Hybrid Representation for High-Resolution 3D Shape Synthesis (nvidia.com) |
| Paper | Deep Marching Tetrahedra: a Hybrid Representation for High-Resolution 3D Shape Synthesis (readpaper.com) |
输入点云或低分辨率体素，提取特征后利用GAN网络，生成每个顶点的位置和SDF偏移值，得到优化后顶点的位置和SDF
结合显式与隐式表达的表示方法，利用MT，从隐式SDF中重建出显式mesh