{"id":20062257,"url":"https://github.com/cuge1995/deep-slam","last_synced_at":"2026-02-25T13:09:02.002Z","repository":{"id":39343928,"uuid":"406552761","full_name":"cuge1995/Deep-SLAM","owner":"cuge1995","description":"a list of papers, code, and other resources focus on deep learning SLAM 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Deep-SLAM\na list of papers, code, dataset and other resources focus on deep learning SLAM sysytem\n\n## Camera\n* DROID-SLAM: Deep Visual SLAM for Monocular, Stereo, and RGB-D Cameras [[code]](https://github.com/princeton-vl/DROID-SLAM)[[paper]](https://arxiv.org/pdf/2108.10869) `NeurIPS 2021 Oral`\n* Deepvo: Towards end-to-end visual odometry with deep recurrent convolutional neural networks [[no code]]()[[paper]](https://arxiv.org/pdf/1709.08429) `ICRA 2017`\n* Unsupervised learning of monocular depth estimation and visual odometry with deep feature reconstruction [[no code]]()[[paper]](https://openaccess.thecvf.com/content_cvpr_2018/papers/Zhan_Unsupervised_Learning_of_CVPR_2018_paper.pdf) `CVPR 2018`\n* Undeepvo: Monocular visual odometry through unsupervised deep learning [[code]](http://senwang.gitlab.io/UnDeepVO)[[paper]](https://arxiv.org/pdf/1709.06841) `ICRA 2018`\n* Deeptam: Deep tracking and mapping [[no code]]()[[paper]](http://openaccess.thecvf.com/content_ECCV_2018/papers/Huizhong_Zhou_DeepTAM_Deep_Tracking_ECCV_2018_paper.pdf) `ECCV 2018`\n* Beyond tracking: Selecting memory and refining poses for deep visual odometry [[no code]]()[[paper]](https://openaccess.thecvf.com/content_CVPR_2019/papers/Xue_Beyond_Tracking_Selecting_Memory_and_Refining_Poses_for_Deep_Visual_CVPR_2019_paper.pdf) `CVPR 2019`\n* Sequential adversarial learning for self-supervised deep visual odometry [[no code]]()[[paper]](https://openaccess.thecvf.com/content_ICCV_2019/papers/Li_Sequential_Adversarial_Learning_for_Self-Supervised_Deep_Visual_Odometry_ICCV_2019_paper.pdf) `ICCV 2019`\n* D2VO: Monocular Deep Direct Visual Odometry [[no code]]()[[paper]](http://ras.papercept.net/images/temp/IROS/files/2025.pdf) `IROS 2020`\n* Deepfactors: Real-time probabilistic dense monocular slam [[no code]]()[[paper]](https://arxiv.org/pdf/2001.05049) `IEEE Robotics and Automation Letters, 2020`\n* Self-supervised deep visual odometry with online adaptation [[no code]]()[[paper]](http://openaccess.thecvf.com/content_CVPR_2020/papers/Li_Self-Supervised_Deep_Visual_Odometry_With_Online_Adaptation_CVPR_2020_paper.pdf) `CVPR 2020`\n* Voldor: Visual odometry from log-logistic dense optical flow residuals [[code]](https://github.com/htkseason/VOLDOR)[[paper]](http://openaccess.thecvf.com/content_CVPR_2020/papers/Min_VOLDOR_Visual_Odometry_From_Log-Logistic_Dense_Optical_Flow_Residuals_CVPR_2020_paper.pdf) `CVPR 2020`\n* TartanVO: A Generalizable Learning-based VO [[code]](https://github.com/castacks/tartanvo)[[paper]](https://arxiv.org/pdf/2011.00359) `CoRL 2020`\n* gradSLAM: Automagically differentiable SLAM, CVPR 2020\n* Generalizing to the Open World: Deep Visual Odometry with Online Adaptation [[no code]]()[[paper]](https://openaccess.thecvf.com/content/CVPR2021/papers/Li_Generalizing_to_the_Open_World_Deep_Visual_Odometry_With_Online_CVPR_2021_paper.pdf) `CVPR 2021`\n* Unsupervised monocular visual odometry based on confidence evaluation [[no code]]()[[paper]](https://ieeexplore.ieee.org/abstract/document/9345430/) `IEEE Transactions on Intelligent Transportation Systems, 2021`\n\n\n\n\n## LiDAR\n* Lo-net: Deep real-time lidar odometry [[no code]]()[[paper]](https://openaccess.thecvf.com/content_CVPR_2019/papers/Li_LO-Net_Deep_Real-Time_Lidar_Odometry_CVPR_2019_paper.pdf) `CVPR 2019`\n* Self-supervised Visual-LiDAR Odometry with Flip Consistency [[no code]]()[[paper]](https://openaccess.thecvf.com/content/WACV2021/papers/Li_Self-Supervised_Visual-LiDAR_Odometry_With_Flip_Consistency_WACV_2021_paper.pdf) `WACV 2021`\n* LoGG3D-Net: Locally Guided Global Descriptor Learning for 3D Place Recognition [code](https://github.com/csiro-robotics/LoGG3D-Net) `ICRA 2022`\n* SHINE-Mapping: Large-Scale 3D Mapping Using Sparse Hierarchical Implicit Neural Representations [code](https://github.com/PRBonn/SHINE_mapping)  `ICRA 2023`\n\n## Dataset\n* [lamar-benchmark](https://github.com/microsoft/lamar-benchmark)  `ECCV 2022`\n* [TartanAir: A Dataset to Push the Limits of Visual SLAM](https://github.com/castacks/tartanvo) `IROS 2020`\n* KITTI Odometry\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcuge1995%2Fdeep-slam","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcuge1995%2Fdeep-slam","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcuge1995%2Fdeep-slam/lists"}