A collection of 3D reconstruction papers in the deep learning era. Feel free to contribute :)
Paper | Representation | Publisher | Project/Code |
---|---|---|---|
3D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstruction | Voxel | ECCV 2016 | Code |
3D Shape Induction from 2D Views of Multiple Objects | Voxel | 3DV 2017 | Code |
Learning Efficient Point Cloud Generation for Dense 3D Object Reconstruction | Point Cloud | AAAI 2018 | Project |
Conditional Single-view Shape Generation for Multi-view Stereo Reconstruction | Point Cloud | CVPR 2019 | Code |
Pixel2Mesh++: Multi-View 3D Mesh Generation via Deformation | Mesh | ICCV 2019 | Project |
Multiview Aggregation for Learning Category-Specific Shape Reconstruction | Point Cloud | NIPS 2019 | Code |
Pix2Surf: Learning Parametric 3D Surface Models of Objects from Images | Patches | ECCV 2020 | Project |
Multi-view 3D Reconstruction with Transformers | Voxel | ICCV 2021 | / |
3D-C2FT: Coarse-to-fine Transformer for Multi-view 3D Reconstruction | Voxel | ACCV 2022 | / |
FvOR: Robust Joint Shape and Pose Optimization for Few-view Object Reconstruction | Implicit | CVPR 2022 | Code |
Paper | Publisher |
---|---|
Image-based 3D Object Reconstruction: State-of-the-Art and Trends in the Deep Learning Era | TPAMI 2019 |
Neural Fields in Visual Computing and Beyond | arXiv 2021 |
Advances in Neural Rendering | EUROGRAPHICS 2022 |
Surface Reconstruction from Point Clouds: A Survey and a Benchmark | arXiv 2022 |
NeRF: Neural Radiance Field in 3D Vision, A Comprehensive Review | arXiv 2022 |
A Review of Deep Learning-Powered Mesh Reconstruction Methods | arXiv 2023 |