Awesome-Learning-MVS
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๐ A list of awesome learning-based multi-view stereo papers
Awesome-Learning-MVS (Methods and Datasets)
Other similar collections
Learning-based MVS Methods
- Volumetric methods (SurfaceNet)
- Depthmap based methods (MVSNet/R-MVSNet and so on)
( ๐ป means code available)
ICCV2017
- ๐ป SurfaceNet: An End-to-end 3D Neural Network for Multiview Stereopsis [paper] [Github] [T-PAMI]
- Learning a Multi-View Stereo Machine [paper] (LSMs can produce two kinds of outputs - voxel occupancy grids decoded from 3D Grid or per-view depth maps decoded after a projection operation.)
- Learned Multi-Patch Similarity [paper] [supp] (Note: Learning to measure multi-image patch similiarity, NOT end-to-end learning MVS pipeline)
CVPR2018
ECCV2018
CVPR2019
ICCV2019
- ๐ป Point-Based Multi-View Stereo Network [paper] [supp] [Github] [T-PAMI] (Point-MVSNet performs multi-view stereo reconstruction in a coarse-to-fine fashion, learning to predict the 3D flow of each point to the groundtruth surface based on geometry priors and 2D image appearance cues)
- P-MVSNet: Learning Patch-wise Matching Confidence Aggregation for Multi-view Stereo [paper]
- MVSCRF: Learning Multi-view Stereo with Conditional Random Fields [paper]
AAAI2020
- Learning Inverse Depth Regression for Multi-View Stereo with Correlation Cost Volume [paper] [Github]
CVPR2020
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๐ป Cascade Cost Volume for High-Resolutoin Multi-View Stereo and Stereo Matching [paper] [Github]
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๐ป Deep Stereo using Adaptive Thin Volume Representation with Uncertainty Awareness [paper] [supp] [Github]
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๐ป Cost Volume Pyramid Based Depth Inference for Multi-View Stereo [paper] [supp] [Github]
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๐ป Fast-MVSNet: Sparse-to-Dense Multi-View Stereo with Learned Propagation and Gauss-Newton Refinement [paper] [supp] [Github]
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Attention-Aware Multi-View Stereo [paper]
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๐ป A Novel Recurrent Encoder-Decoder Structure for Large-Scale Multi-view Stereo Reconstruction from An Open Aerial Dataset [paper] [Github] [data]
ECCV2020
- ๐ป Pyramid Multi-view Stereo Net with Self-adaptive View aggregation [paper] [Github]
- ๐ป Dense Hybird Recurrent Multi-view Stereo Net with Dynamic Consistency Checking [paper] [Github]
BMVC2020
WACV2021
- Long-range Attention Network for Multi-View Stereo [paper]
CVPR2021
ICCV2021
- ๐ป AA-RMVSNet: Adaptive Aggregation Recurrent Multi-view Stereo Network [paper] [supp] [Github]
- EPP-MVSNet: Epipolar-Assembling Based Depth Prediction for Multi-View Stereo [paper]
- Just a Few Points are All You Need for Multi-view Stereo: A Novel Semi-supervised Learning Method for Multi-view Stereo [paper] [supp]
3DV 2021
CVPR 2022
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๐ป IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo [paper] [supp] [Github]
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๐ป Rethinking Depth Estimation for Multi-View Stereo: A Unified Representation and Focal Loss [paper][supp] [Github]
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๐ป RayMVSNet: Learning Ray-Based 1D Implicit Fields for Accurate Multi-View Stereo [paper] [supp] [Github]
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๐ป Non-Parametric Depth Distribution Modelling Based Depth Inference for Multi-View Stereo [paper] [supp]
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๐ป TransMVSNet: Global Context-aware Multi-view Stereo Network with Transformers [paper] [supp] [Github]
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๐ป Generalized Binary Search Network for Highly-Efficient Multi-View Stereo [paper] [supp] [Github]
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Efficient Multi-View Stereo by Iterative Dynamic Cost Volume [paper] [supp]
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๐ป MVS2D: Efficient Multi-view Stereo via Attention-Driven 2D Convolutions [paper] [supp] [Github]
ECCV 2022
- ๐ป MVSTER: Epipolar Transformer for Efficient Multi-View Stereo [paper] [Github]
- ๐ป Multiview Stereo with Cascaded Epipolar RAFT [paper] [Github]
To Be Continued
Journal Paper
- MVSNet++: Learning Depth-Based Attention Pyramid Features for Multi-View Stereo. IEEE TIP [paper]
- HighRes-MVSNet: A Fast Multi-View Stereo Network for Dense 3D Reconstruction From High-Resolution Images. IEEE Access [paper]
- ๐ป AACVP-MVSNet: Attention-aware cost volume pyramid based multi-view stereo network for 3D reconstruction. ISPRS Journal of Photogrammetry and Remote Sensing [paper] [Github]
- Learning Inverse Depth Regression for Pixelwise Visibility-Aware Multi-View Stereo Networks. IJCV [paper]
Survey Paper
- A Survey on Deep Learning Techniques for Stereo-based Depth Estimation. IEEE T-PAMI [ArXiv] [IEEE Xplore]
- Deep Learning for Multi-view Stereo via Plane Sweep: A Survey [paper]
- Multi-view stereo in the Deep Learning Era: A comprehensive revfiew [paper]
ArXiv Paper
- PVSNet: Pixelwise Visibility-Aware Multi-View Stereo Network [paper]
- DDR-Net: Learning Multi-Stage Multi-View Stereo With Dynamic Depth Range [paper] [Github]
- Non-local Recurrent Regularization Networks for Multi-view Stereo [paper]
Multi-view Stereo Benchmark
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Middlebury [CVPR06']
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EPFL [CVPR08']
- On Benchmarking Camera Calibration and Multi-View Stereo for High Resolution Imagery [paper]
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DTU [CVPR2014, IJCV2016]
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Tanks and Temples [ACM ToG2017]
- Tanks and Temples: Benchmarking Large-Scale Scene Reconstruction [paper] [supp] [website] [Github] [leaderboard]
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ETH3D [CVPR2017]
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BlendedMVS [CVPR2020]
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GigaMVS [T-PAMI2021]
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Multi-sensor large-scale dataset for multi-view 3D reconstruction [ArXiv2022]
Large-scale Real-world Scenes
- Chinese Style Architectures
- http://vision.ia.ac.cn/zh/data/index.html, provided by CASIA.
- Western Style Architectures
- https://colmap.github.io/datasets.html, provided by COLMAP.
- ImageDataset_SceauxCastle, provided by OpenMVG.
- Aerial Dataset
- http://gpcv.whu.edu.cn/data/WHU_MVS_Stereo_dataset.html, provided by WHU.
Update: WeChat Group
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