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)

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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

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不足:

  • 对未见视图的重建质量不高
  • 只支持低分辨率图像和三平面
  • 只支持输入没有背景的物体图像
  • 没用到任何先验知识
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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)

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THUman2.0数据集demo结果好(除手、脸和脚),训练代码还未开源
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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)

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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

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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)

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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

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Title TransHuman: A Transformer-based Human Representation for Generalizable Neural Human Rendering
Author Xiao Pan1,2,∗, Zongxin Yang1, Jianxin Ma2, Chang Zhou2, Yi Yang1,†
Conf/Jour ICCV
Year 2023
Project TransHuman: A Transformer-based Human Representation for Generalizable Neural Human Rendering (pansanity666.github.io)
Paper TransHuman: A Transformer-based Human Representation for Generalizable Neural Human Rendering (readpaper.com)

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Paper Model Input Parameter/Pnum GPU
DiT-3D Diffusion Transformers Voxelized PC
PointFlow AE flow-based PointCloud 1.61M
FlowGAN GAN flow-based Single Image N = 2500 A40 45GB
BuilDiff Diffusion models Single Image 1024 to 4096 A40 45GB
CCD-3DR CDPM Single Image 8192 3090Ti 24GB
SG-GAN SG-GAN Single Image
HaP Diffusion+SMPL+DepthEstimation Single Image 10000 4x3090Ti
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Title BuilDiff: 3D Building Shape Generation using Single-Image Conditional Point Cloud Diffusion Models
Author Wei, Yao and Vosselman, George and Yang, Michael Ying
Conf/Jour ICCV
Year 2023
Project weiyao1996/BuilDiff: BuilDiff: 3D Building Shape Generation using Single-Image Conditional Point Cloud Diffusion Models (github.com)
Paper BuilDiff: 3D Building Shape Generation using Single-Image Conditional Point Cloud Diffusion Models (readpaper.com)

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  • 关注建筑物的重建,为 3D Diffusion Models 中添加了图片的信息嵌入(预训练了一个图片编码器)
  • 两阶段的点云降噪模型,第一阶段关注全局,第二阶段关注细节
  • 提出了两个自定义的新数据集,并在数据集上验证了本方法的优点
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Title Flow-based GAN for 3D Point Cloud Generation from a Single Image
Author Yao Wei (University of Twente), George Vosselman (“University of Twente, the Netherlands”), Michael Ying Yang (University of Twente)*
Conf/Jour BMVA
Year 2022
Project Flow-based GAN for 3D Point Cloud Generation from a Single Image (mpg.de)
Paper Flow-based GAN for 3D Point Cloud Generation from a Single Image (readpaper.com)

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  • flow-based explicit generative models for sampling point clouds with arbitrary resolutions
  • Improving the detailed 3D structures of point clouds by leveraging the implicit generative adversarial networks (GANs).
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