{"id":17052983,"url":"https://github.com/natowi/3d-reconstruction-with-deep-learning-methods","last_synced_at":"2026-02-11T10:33:27.999Z","repository":{"id":41402805,"uuid":"166886300","full_name":"natowi/3D-Reconstruction-with-Deep-Learning-Methods","owner":"natowi","description":"List of projects for 3d 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unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["3d-reconstruction","deep-learning","deep-neural-networks","depth-estimation","depth-prediction","list"],"created_at":"2024-10-14T10:11:04.496Z","updated_at":"2026-02-11T10:33:27.964Z","avatar_url":"https://github.com/natowi.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# 3D-Reconstruction-with-Deep-Learning-Methods\n\nThe focus of this list is on open-source projects hosted on Github.\n\n**Projects released on Github**\n\n| TITLE                                                        | KEYWORDS                    | URL                                                          | LICENSE                                                      | Awesomeness |\n| ------------------------------------------------------------ | --------------------------- | ------------------------------------------------------------ | ------------------------------------------------------------ | ----------- |\n| High Quality Monocular Depth Estimation via Transfer Learning | TensorFlow, PyTorch         | https://github.com/ialhashim/DenseDepth https://arxiv.org/abs/1812.11941 | GPL-3.0                                                      |             |\n| Multi-view stereo image-based 3D reconstruction              |                             | https://github.com/adahbingee/pais-mvs                       | nn                                                           |             |\n| Hybrid Ensemble Approach For 3D Object Reconstruction from Multi-View Monocular RGB images |                             | https://github.com/Ajithbalakrishnan/3D-Object-Reconstruction-from-Multi-View-Monocular-RGB-images | nn                                                           |             |\n| Deep 3D Semantic Scene Extrapolation                         | hybrid CNN, GAN, TensorFlow | https://github.com/AliAbbasi/Deep-3D-Semantic-Scene-Extrapolation http://user.ceng.metu.edu.tr/~ys/pubs/extrap-tvcj18.pdf | nn                                                           |             |\n| ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans | TensorFlow                  | https://github.com/angeladai/ScanComplete                    | Apache-2.0                                                   |             |\n| AtLoc: Attention Guided Camera Localization                  | PyTorch                     | https://github.com/BingCS/AtLoc https://arxiv.org/abs/1909.03557 | BY-NC-SA 4.0                                                 |             |\n| PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation | TensorFlow, cuDNN           | https://github.com/charlesq34/pointnet                       | MIT License                                                  |             |\n| PyTorch Implementation of DeepVO                             | PyTorch, CNN                | https://github.com/ChiWeiHsiao/DeepVO-pytorch                | nn                                                           |             |\n| Fully Convolutional Geometric Features: Fast and accurate 3D features for registration and correspondence. | PyTorch                     | https://github.com/chrischoy/FCGF                            | MIT License                                                  |             |\n| Morphing and Sampling Network for Dense Point Cloud Completion (AAAI2020) | PyTorch                     | https://github.com/Colin97/MSN-Point-Cloud-Completion        | Apache-2.0                                                   |             |\n| Real-Time Self-Adaptive Deep Stereo                          | TensorFlow                  | https://github.com/CVLAB-Unibo/Real-time-self-adaptive-deep-stereo | Apache-2.0                                                   |             |\n| Geometry meets semantics for semi-supervised monocular depth estimation - ACCV 2018 | TensorFlow                  | https://github.com/CVLAB-Unibo/Semantic-Mono-Depth           | MIT License                                                  |             |\n| BlenderProc: A procedural blender pipeline to generate images for deep learning |  Blender                    | https://github.com/DLR-RM/BlenderProc                        | GPL-3.0                                                      |             |\n| SingleViewReconstruction: 3D Scene Reconstruction from a Single Viewport |  TensorFlow               | https://github.com/DLR-RM/SingleViewReconstruction                        | MIT License                                                      |             |\n| NNCAP — Neural Network Complex Approach to Photogrammetry    |                             | https://github.com/Dok11/nn-dldm                             | nn                                                           |             |\n| Pytorch Implementation of Deeper Depth Prediction with Fully Convolutional Residual Networks | PyTorch                     | https://github.com/dontLoveBugs/FCRN_pytorch                 | nn                                                           |             |\n| Improved Adversarial Systems for 3D Object Generation and Reconstruction | GAN                         | https://github.com/EdwardSmith1884/3D-IWGAN                  | MIT License                                                  |             |\n| Deep Learning for Visual-Inertial Odometry                   | PyTorch, CNN                | https://github.com/ElliotHYLee/Deep_Visual_Inertial_Odometry | MIT License                                                  |             |\n| Machine Vision                                               | List                        | https://github.com/Ewenwan/MVision                           | nn                                                           |             |\n| Mesh R-CNN, an academic publication, presented at ICCV 2019  | PyTorch, R-CNN              | https://github.com/facebookresearch/meshrcnn                 | BSD-3-Clause License                                         |             |\n| PyTorch3d is FAIR's library of reusable components for deep learning with 3D data. | PyTorch                     | https://github.com/facebookresearch/pytorch3d                | BSD-3-Clause License                                         |             |\n| Self-supervised Sparse-to-Dense: Self-supervised Depth Completion from LiDAR and Monocular Camera | PyTorch                     | https://github.com/fangchangma/self-supervised-depth-completion | MIT License                                                  |             |\n| Sparse-to-Dense: Depth Prediction from Sparse Depth Samples and a Single Image | PyTorch                     | https://github.com/fangchangma/sparse-to-dense               | BSD License                                                  |             |\n| Sparse-to-Dense: Depth Prediction from Sparse Depth Samples and a Single Image | PyTorch                     | https://github.com/fangchangma/sparse-to-dense.pytorch       | nn                                                           |             |\n| PackNet-SfM: 3D Packing for Self-Supervised Monocular Depth Estimation | PyTorch                     | https://github.com/FangGet/PackNet-SFM-PyTorch               | GPL-3.0                                                      |             |\n| InvSFM: Revealing Scenes by Inverting Structure from Motion Reconstructions [CVPR 2019] | TensorFlow                  | https://github.com/francescopittaluga/invsfm                 | MIT License                                                  |             |\n| Deep Monocular Visual Odometry using PyTorch (Experimental)  | PyTorch                     | https://github.com/fshamshirdar/DeepVO                       | nn                                                           |             |\n| PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation | PyTorch                     | https://github.com/fxia22/pointnet.pytorch                   | MIT License                                                  |             |\n| Pix2Depth - Depth Map Estimation from Monocular Image        | Keras                       | https://github.com/gautam678/Pix2Depth                       | GPL-3.0                                                      |             |\n| 3DRegNet: A Deep Neural Network for 3D Point Registration    | TensorFlow                  | https://github.com/goncalo120/3DRegNet                       | MIT License                                                  |             |\n| Neural 3D Mesh Renderer – Single-Image 3D Reconstruction using Neural Renderer |                             | https://github.com/hiroharu-kato/mesh_reconstruction         | MIT License                                                  |             |\n| Real-time Scalable Dense Surfel Mapping                      |                             | https://github.com/HKUST-Aerial-Robotics/DenseSurfelMapping  | nn                                                           |             |\n| MVDepthNet: real-time multiview depth estimation neural network | PyTorch                     | https://github.com/HKUST-Aerial-Robotics/MVDepthNet          | nn                                                           |             |\n| DeepMatchVO: Beyond Photometric Loss for Self-Supervised Ego-Motion Estimation |                             | https://github.com/hlzz/DeepMatchVO                          | MIT License                                                  |             |\n| MIRorR: Matchable Image Retrieval by Learning from Surface Reconstruction | TensorFlow, CNN             | https://github.com/hlzz/mirror                               | MIT License                                                  |             |\n| Unsupervised Learning of Monocular Depth Estimation and Visual Odometry with Deep Feature Reconstruction | Caffe                       | https://github.com/Huangying-Zhan/Depth-VO-Feat              | non-commercial                                               |             |\n| Deep Learning 3D vision papers                               | papers, list, CN            | https://github.com/huayong/dl-vision-papers                  | nn                                                           |             |\n| Open3D PointNet implementation with PyTorch                  | PyTorch, jupyter, Open3D    | https://github.com/intel-isl/Open3D-PointNet                 | MIT License                                                  |             |\n| Semantic-TSDF for Self-driving Static Scene Reconstruction   | PyTorch                     | https://github.com/irsisyphus/semantic-tsdf                  | MIT License                                                  |             |\n| Weakly supervised 3D Reconstruction with Adversarial Constraint |                             | https://github.com/jgwak/McRecon                             | MIT License                                                  |             |\n| Using Deep learning Technique for Stereo vision and 3D reconstruction | TensorFlow, CN              | https://github.com/jiafeng5513/EvisionNet                    | nn                                                           |             |\n| Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video | PyTorch                     | https://github.com/JiawangBian/SC-SfMLearner-Release         | GPL-3.0                                                      |             |\n| Revisiting Single Image Depth Estimation: Toward  Higher Resolution Maps with Accurate Object Boundaries (official  implementation) | PyTorch                     | https://github.com/JunjH/Revisiting_Single_Depth_Estimation  | nn                                                           |             |\n| Visualization of Convolutional Neural Networks for Monocular Depth Estimation (official  implementation) | CNN, PyTorch                | https://github.com/JunjH/Visualizing-CNNs-for-monocular-depth-estimation | MIT License                                                  |             |\n| DeepVO: Towards End-to-End Visual Odometry with Deep Recurrent Convolutional Neural Networks | PyTorch                     | https://github.com/krrish94/DeepVO                           | nn                                                           |             |\n| DISN: Deep Implicit Surface Network for High-quality Single-view 3D Reconstruction | Tensorflow                  | https://github.com/laughtervv/DISN                           | nn                                                           |             |\n| DeepTAM: Deep Tracking and Mapping                           |                             | https://github.com/lmb-freiburg/deeptam                      | GPL-3.0                                                      |             |\n| DeMoN: Depth and Motion Network                              | Tensorflow                  | https://github.com/lmb-freiburg/demon                        | GPL-3.0                                                      |             |\n| PyTorch implementation of CloudWalk's recent work DenseBody  | PyTorch                     | https://github.com/Lotayou/densebody_pytorch                 | GPL-3.0                                                      |             |\n| Self-supervised learning for dense depth estimation in monocular endoscopy | Tensorflow, Torch           | https://github.com/lppllppl920/EndoscopyDepthEstimation-Pytorch | non-commercial                                               |             |\n| ContextDesc: Local Descriptor Augmentation with Cross-Modality Context | Tensorflow                  | https://github.com/lzx551402/contextdesc                     | nn                                                           |             |\n| GL3D (Geometric Learning with 3D Reconstruction): a  large-scale database created for 3D reconstruction and geometry-related  learning problems |                             | https://github.com/lzx551402/GL3D                            | MIT License                                                  |             |\n| Deeper Depth Prediction with Fully Convolutional Residual Networks (official implementation) | Tensorflow                  | https://github.com/MahmoudSelmy/DeeperDepthEstimation        | nn                                                           |             |\n| Fine-Tuning Vgg16 For Depth Estimation                       | Tensorflow                  | https://github.com/MahmoudSelmy/DepthEstimationVGG           | nn                                                           |             |\n| 3D reconstruction with neural networks using Tensorflow. See link for Video |                             | https://github.com/micmelesse/3D-reconstruction-with-Neural-Networks | nn                                                           |             |\n| Learning Depth from Monocular Videos using Direct Methods    | PyTorch                     | https://github.com/MightyChaos/LKVOLearner                   | BSD-3-Clause                                                 |             |\n| PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition | Tensorflow                  | https://github.com/mikacuy/pointnetvlad                      | MIT License                                                  |             |\n| Attempting to estimate topography of a region from image data |                             | https://github.com/nbelakovski/topography_neural_net         | nn                                                           |             |\n| DDRNet: Depth Map Denoising and Refinement for Consumer Depth Cameras Using Cascaded CNNs | Tensorflow                  | https://github.com/neycyanshi/DDRNet                         | MIT License                                                  |             |\n| Monocular depth estimation from a single image               | PyTorch                     | https://github.com/nianticlabs/monodepth2                    | Copyright © Niantic, Inc. 2018. Patent Pending - non-commercial use only |             |\n| 3D-RelNet: Joint Object and Relation Network for 3D prediction | Torch, jupyter              | https://github.com/nileshkulkarni/relative3d                 | nn                                                           |             |\n| PlaneRCNN detects and reconstructs piece-wise planar surfaces from a single RGB image | Torch, RCNN                 | https://github.com/NVlabs/planercnn                          | Copyright (c) 2018 NVIDIA Corp.  All Rights Reserved. This work is licensed under the [Creative Commons Attribution NonCommercial ShareAlike 4.0 License](https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode). |             |\n| OctoMap - An Efficient Probabilistic 3D Mapping Framework Based on Octrees. |                             | https://github.com/OctoMap/octomap                           | University of Freiburg, Copyright (C) 2009-2014, octomap: New BSD License, octovis and related libraries: GPL |             |\n| Unsupervised Monocular Depth Estimation neural network MonoDepth in PyTorch (Unofficial implementation) | PyTorch                     | https://github.com/OniroAI/MonoDepth-PyTorch                 | nn                                                           |             |\n| Learning to Sample: A learned sampling approach for point clouds |                             | https://github.com/orendv/learning_to_sample                 | MIT License                                                  |             |\n| DeepMVS: Learning Multi-View Stereopsis                      | CNN, PyTorch                | https://github.com/phuang17/DeepMVS                          | BSD 2-clause                                                 |             |\n| DeepV2D: Video to Depth with Differentiable Structure from Motion | Tensorflow                  | https://github.com/princeton-vl/DeepV2D                      | nn                                                           |             |\n| High Quality Monocular Depth Estimation via Transfer Learning | Tensorflow                  | https://github.com/priya-dwivedi/Deep-Learning/tree/master/depth_estimation | nn (GPL-3.0 ?)                                               |             |\n| Deep Single-View 3D Object Reconstruction with Visual Hull Embedding | CNN, Tensorflow             | https://github.com/qweas120/PSVH-3d-reconstruction           | MIT License                                                  |             |\n| ScanNet is an RGB-D video dataset containing 2.5 million views in more than 1500 scans, annotated with 3D camera poses,... |                             | https://github.com/ScanNet/ScanNet                           | Can be used with the restriction to give credit and include original Copyright |             |\n| Visual inspection of bridges is customarily used to identify and evaluate faults | CNN                         | https://github.com/Shaggyshak/CS543_project_Image-based-Localization-of-Bridge-Defects-with-AR-Visualization | nn                                                           |             |\n| Semantic 3D Occupancy Mapping through Efficient High Order CRFs | CNN                         | https://github.com/shichaoy/semantic_3d_mapping              | BSD-3-Clause                                                 |             |\n| Factoring Shape, Pose, and Layout from the 2D Image of a 3D Scene |                             | https://github.com/shubhtuls/factored3d                      | nn                                                           |             |\n| Motion R-CNN codebase (old)                                  | RCNN                        | https://github.com/simonmeister/old-motion-rcnn              | MIT License                                                  |             |\n| Geometry-Aware Symmetric Domain Adaptation for Monocular Depth Estimation | PyTorch                     | https://github.com/sshan-zhao/GASDA                          | nn                                                           |             |\n| 3D Scene Graph: A Structure for Unified Semantics, 3D Space, and Camera |                             | https://github.com/StanfordVL/3DSceneGraph                   | MIT License                                                  |             |\n| Minkowski Engine is an auto-diff convolutional neural network library for high-dimensional sparse tensors | PyTorch                     | https://github.com/stanfordvl/MinkowskiEngine                | MIT License                                                  |             |\n| Learning Single-View 3D Reconstruction with Limited Pose Supervision (Official implementation) | Tensorflow                  | https://github.com/stevenygd/3d-recon                        | MIT License                                                  |             |\n| VNect: Real-time 3D Human Pose Estimation with a Single RGB Camera (Tensorflow version) | Tensorflow                  | https://github.com/timctho/VNect-tensorflow                  | Apache-2.0                                                   |             |\n| 3D-LMNet: Latent Embedding Matching for Accurate and Diverse 3D Point Cloud Reconstruction from a Single Image |                             | https://github.com/val-iisc/3d-lmnet                         | MIT License                                                  |             |\n| Learning to Find Good Correspondences                        |                             | https://github.com/vcg-uvic/learned-correspondence-release   | For reserch and evaluation only. Commercial usage requires written approval |             |\n| A Framework for the Volumetric Integration of Depth Images   |                             | https://github.com/victorprad/InfiniTAM                      | non-commercial                                               |             |\n| Pixel2Mesh++: Multi-View 3D Mesh Generation via Deformation  | Tensorflow                  | https://github.com/walsvid/Pixel2MeshPlusPlus                | BSD-3-Clause                                                 |             |\n| Adversarial Semantic Scene Completion from a Single Depth Image (Official implementation) | Tensorflow                  | https://github.com/wangyida/gan-depth-semantic3d             | nn                                                           |             |\n| SurfelWarp: Efficient Non-Volumetric Dynamic Reconstruction  |                             | https://github.com/weigao95/surfelwarp                       | BSD-3-Clause                                                 |             |\n| PCN: Point Completion Network                                | Tensorflow                  | https://github.com/wentaoyuan/pcn                            | MIT License                                                  |             |\n| DISN: Deep Implicit Surface Network for High-quality Single-view 3D Reconstruction |                             | https://github.com/Xharlie/DISN                              | nn                                                           |             |\n| Real-time motion from structure                              | CNN                         | https://github.com/yan99033/CNN-SVO                          | nn                                                           |             |\n| Dense 3D Object Reconstruction from a Single Depth View      | Tensorflow                  | https://github.com/Yang7879/3D-RecGAN-extended               | MIT License                                                  |             |\n| Semi-supervised monocular depth map prediction               | Tensorflow                  | https://github.com/Yevkuzn/semodepth                         | GPL-3.0                                                      |             |\n| 3DFeat-Net: Weakly Supervised Local 3D Features for Point Cloud Registration | Tensorflow                  | https://github.com/yewzijian/3DFeatNet                       | MIT License                                                  |             |\n| Estimated Depth Map Helps Image Classification: Depth estimation with neural network, and learning on RGBD images |                             | https://github.com/yihui-he/Estimated-Depth-Map-Helps-Image-Classification | MIT License                                                  |             |\n| Fit 3DMM to front and side face images simultaneously.       |                             | https://github.com/Yinghao-Li/3DMM-fitting                   | nn                                                           |             |\n| The Perfect Match: 3D Point Cloud Matching with Smoothed Densities | CNN, Tensorflow             | https://github.com/zgojcic/3DSmoothNet                       | BSD-3-Clause                                                 |             |\n| NeurVPS: Neural Vanishing Point Scanning via Conic Convolution | Tenosorflow                 | https://github.com/zhou13/neurvps                            | MIT License                                                  |             |\n| LayoutNet: Reconstructing the 3D Room Layout from a Single RGB Image (Torch implementation) | Torch                       | https://github.com/zouchuhang/LayoutNet                      | MIT License                                                  |             |\n| NeRF: Neural Radiance Fields                                 |                             | https://github.com/bmild/nerf                                | MIT License                                                  | 10          |\n| Local Light Field Fusion at SIGGRAPH 2019                    |                             | https://github.com/fyusion/llff                              | GPL-3.0                                                      | 10          |\n| neural-volumes-learning-dynamic-renderable-volumes-from-images |                             | https://research.fb.com/publications/neural-volumes-learning-dynamic-renderable-volumes-from-images/\u003cbr/\u003ehttps://github.com/facebookresearch/neuralvolumes | BY-NC 4.0                                                    |             |\n| Learning Less is More - 6D Camera Localization via 3D Surface Regression |                             | https://github.com/vislearn/LessMore                         | BSD-3-Clause                                                 |             |\n| Local features                                               |                             | https://github.com/vcg-uvic/lf-net-release                   |                                                              |             |\n| Pix2Vox                                                      |                             | https://github.com/hzxie/Pix2Vox                             |                                                              |             |\n| PlanarReconstruction: Single-Image Piece-wise Planar 3D Reconstruction via Associative Embedding | pytorch                     | https://github.com/svip-lab/PlanarReconstruction             |                                                              |             |\n| Depth estimation with deep Neural networks                   |                             | https://medium.com/@omarbarakat1995/depth-estimation-with-deep-neural-networks-part-1-5fa6d2237d0d\u003cbr/\u003ehttps://medium.com/datadriveninvestor/depth-estimation-with-deep-neural-networks-part-2-81ee374888eb\u003cbr/\u003ehttps://github.com/MahmoudSelmy/DeeperDepthEstimation\u003cbr/\u003ehttps://github.com/MahmoudSelmy/DepthEstimationVGG/blob/master/README.md |                                                              |             |\n| High Quality Monocular Depth Estimation via Transfer Learning |                             | https://github.com/ialhashim/DenseDepth\u003cbr /\u003ehttps://arxiv.org/abs/1812.11941 |                                                              |             |\n| D3Feat                                                        |                             | https://github.com/XuyangBai/D3Feat               |                                                               |             |\n| Hierarchical Deep Stereo Matching on High Resolution Images  | pytorch           | https://github.com/gengshan-y/high-res-stereo                | MIT          |             |\n| Structure-Aware Residual Pyramid Network for Monocular Depth Estimation | pytorch           | https://github.com/Xt-Chen/SARPN                             | nn           |             |\n| Pytorch code to construct a 3D point cloud model from single RGB image. | pytorch           | https://github.com/lkhphuc/pytorch-3d-point-cloud-generation | nn           |             |\n| Depth estimation from RGB images using fully convolutional neural networks | pytorch           | https://github.com/karoly-hars/DE_resnet_unet_hyb            | BSD-3-Clause |             |\n| Single-Image Piece-wise Planar 3D Reconstruction via Associative Embedding | torch, tensorflow | https://github.com/svip-lab/PlanarReconstruction             | MIT          |             |\n| TriDepth: Triangular Patch-based Deep Depth Prediction       | PyTorch           | https://github.com/syinari0123/tridepth                      | MIT          |             |\n| Depth Map Prediction from a Single Image using a Multi-Scale Deep Network | torch             | https://github.com/imran3180/depth-map-prediction            | nn           |             |\n| Hybrid CNN for Single Image Depth Estimation                 | torch             | https://github.com/karoly-hars/DE_resnet_unet_hyb            | BSD-3-Clause |             |\n| MarrNet: 3D Shape Reconstruction via 2.5D Sketches           | torch             | https://github.com/jiajunwu/marrnet                          | nn           |             |\n| Consistent Video Depth Estimation                            |                   | https://roxanneluo.github.io/Consistent-Video-Depth-Estimation/ | nn           |             |\n| HF-Net: Robust Hierarchical Localization at Large Scale      | torch, tensorflow | https://github.com/ethz-asl/hfnet                            | MIT          |             |\n| Hierarchical Deep Stereo Matching on High Resolution Images  | pytorch           | https://github.com/gengshan-y/high-res-stereo                | MIT          |             |\n| Structure-Aware Residual Pyramid Network for Monocular Depth Estimation | pytorch           | https://github.com/Xt-Chen/SARPN                             | nn           |             |\n| Pytorch code to construct a 3D point cloud model from single RGB image. | pytorch           | https://github.com/lkhphuc/pytorch-3d-point-cloud-generation | nn           |             |\n| Depth estimation from RGB images using fully convolutional neural networks | pytorch           | https://github.com/karoly-hars/DE_resnet_unet_hyb            | BSD-3-Clause |             |\n| Single-Image Piece-wise Planar 3D Reconstruction via Associative Embedding | torch, tensorflow | https://github.com/svip-lab/PlanarReconstruction             | MIT          |             |\n| TriDepth: Triangular Patch-based Deep Depth Prediction       | PyTorch           | https://github.com/syinari0123/tridepth                      | MIT          |             |\n| Depth Map Prediction from a Single Image using a Multi-Scale Deep Network | torch             | https://github.com/imran3180/depth-map-prediction            | nn           |             |\n| Hybrid CNN for Single Image Depth Estimation                 | torch             | https://github.com/karoly-hars/DE_resnet_unet_hyb            | BSD-3-Clause |             |\n| MarrNet: 3D Shape Reconstruction via 2.5D Sketches           | torch             | https://github.com/jiajunwu/marrnet                          | nn           |             |\n| Consistent Video Depth Estimation                            |                   | https://roxanneluo.github.io/Consistent-Video-Depth-Estimation/ | nn           |             |\n| HF-Net: Robust Hierarchical Localization at Large Scale      | torch, tensorflow | https://github.com/ethz-asl/hfnet                            | MIT          |             |\n\n\n\n**Other Projects**\n\n| TITLE                                                        | KEYWORDS              | URL                                                          | LICENSE |\n| ------------------------------------------------------------ | --------------------- | ------------------------------------------------------------ | ------- |\n| 3D-Scene-GAN: Three-dimensional Scene Reconstruction with Generative Adversarial Networks | paper                 | https://openreview.net/forum?id=SkNEsmJwf                    |         |\n| Google: Deep Learning Depth Prediction                       | magazine article, GER | https://www.digitalproduction.com/2019/05/27/google-deep-learning-depth-prediction/ |         |\n| SLAM and Deep Leraning for 3D Indoor Scene Understanding     | PhD thesis            | https://www.doc.ic.ac.uk/~ajd/Publications/McCormac-J-2019-PhD-Thesis.pdf |         |\n| Dense 3D Object Reconstruction from a Single Depth View      | 3D-RecGAN++           | https://arxiv.org/abs/1802.00411                             |         |\n| Moving Camera, Moving People: A Deep Learning Approach to Depth Prediction |                       | https://ai.googleblog.com/2019/05/moving-camera-moving-people-deep.html |         |\n| Depth Estimation from a Single RGB Image                     |                       | http://campar.in.tum.de/Chair/ProjectDepthPrediction         |         |\n| Deep Fundamental Matrix Estimation                           |                       | http://vladlen.info/papers/deep-fundamental.pdf              |         |\n| depth_estimation                                             |                       | https://towardsdatascience.com/depth-estimation-on-camera-images-using-densenets-ac454caa893 |         |\n| **3D-Machine-Learning List**                                 |                       | https://github.com/timzhang642/3D-Machine-Learning           |         |\n| **DEEP LEARNING-BASED 3D OBJECT RECONSTRUCTION - A SURVEY - Image-based 3D Object Reconstruction:State-of-the-Art and Trends in the DeepLearning Era** |                       | https://arxiv.org/pdf/1906.06543.pdf                         |         |\n|                                                              |                       |                                                              |         |\n|                                                              |                       |                                                              |         |\n|                                                              |                       |                                                              |         |\n|                                                              |                       |                                                              |         |\n\nI2-SDF: Intrinsic Indoor Scene Reconstruction and Editing via Raytracing in Neural SDFs (CVPR 2023) https://github.com/jingsenzhu/i2-sdf MIT \n\nhttps://github.com/lioryariv/idr\n\nhttps://github.com/autonomousvision/differentiable_volumetric_rendering\n\nhttps://github.com/Dok11/surface-match-dataset\n\nImage-based 3D Object Reconstruction:State-of-the-Art and Trends in the DeepLearning Era https://arxiv.org/pdf/1906.06543v3.pdf\n\nDense 3D Object Reconstructionfrom a Single Depth View https://arxiv.org/pdf/1802.00411v2.pdf\n\nhttps://dagshub.com/OperationSavta/SavtaDepth https://colab.research.google.com/drive/1XU4DgQ217_hUMU1dllppeQNw3pTRlHy1?usp=sharing https://huggingface.co/spaces/kingabzpro/savtadepth MIT License\n\nhttps://github.com/gradslam/gradslam pyTorch\n\nhttps://github.com/ventusff/neurecon\n\nhttps://github.com/theICTlab/3DUNDERWORLD-SLS-GPU_CPU\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnatowi%2F3d-reconstruction-with-deep-learning-methods","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnatowi%2F3d-reconstruction-with-deep-learning-methods","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnatowi%2F3d-reconstruction-with-deep-learning-methods/lists"}