Self-Supervised depth kalilia
Conference | Tittle | code | Author | mark | note |
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NIPS2020 | Forget About the LiDAR: Self-Supervised Depth Estimators with MED Probability Volumes | Korea Advanced Institute of Science and Technology | 🙉 | link | |
CVPR2021 | DRO: Deep Recurrent Optimizer for Structure-from-Motion | Alibaba A.I. Labs | 🙈 | link | |
CVPR2021 | The Temporal Opportunist: Self-Supervised Multi-Frame Monocular Depth | link | Niantic | 🙈 | |
CVPR2020 | Self-supervised Monocular Trained Depth Estimation using Self-attention and Discrete Disparity Volume | link | Australian Institute for Machine Learning | 🙈 | |
ECCV2020 | Feature-metric Loss for Self-supervised Learning of Depth and Egomotion | link | 🙈 |
Conference | Tittle | code | Author | mark | note |
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CVPR2017 | Semi-Supervised Deep Learning for Monocular Depth Map Prediction | RWTH Aachen University | 🙈 | ||
CVPR2017 | SfMLearner: Unsupervised Learning of Depth and Ego-Motion from Video | link | UC Berkeley | ⭐ | link |
Conference | Tittle | code | Author | mark | note |
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CVPR2018 | DVO: Learning Depth from Monocular Videos using Direct Methods | Carnegie Mellon University | 🙈 | ||
CVPR2018 | GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose | link | SenseTime Research | 🙈 | |
ECCV2018 | DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Task Consistency | ) | Virginia Tech | 🙈 |
Conference | Tittle | code | Author | mark | note |
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2019 | Self-Supervised 3D Keypoint Learning for Ego-motion Estimation | Toyota Research Institute (TRI) | 🙈 | ||
ICRA2019 | SuperDepth: Self-Supervised, Super-Resolved Monocular Depth Estimation | Toyota Research Institute (TRI) | 🙈 | ||
AAAI2019 | Depth prediction without the sensors: Leveraging structure for unsupervised learning from monocular videos | Harvard University/Google Brain | 🙈 | ||
ICCV2019 | Unsupervised High-Resolution Depth Learning From Videos With Dual Networks | Tsinghua University | 🙈 | ||
ICCV2019 | Self-Supervised Monocular Depth Hints | link | Niantic | 🙈 | |
ICCV2019 | Monodepth2: Digging into self-supervised monocular depth estimation | link | UCL/niantic | 🙈 | |
NIPS2019 | SC-SfMLearner: Unsupervised scale-consistent depth and ego-motion learning from monocular video | University of Adelaide, Australia | 🙈 | ||
CVPR2019 | Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion Segmentation | Max Planck Institute for Intelligent Systems | 🙈 |
Conference | Tittle | code | Author | mark |
---|---|---|---|---|
ECCV2016 | Unsupervised CNN for Single View Depth Estimation: Geometry to the Rescue | University of Adelaide | 🙈 | |
CVPR2017 | DispNet: Unsupervised Monocular Depth Estimation with Left-Right Consistency | University College London | 🙈 | |
Cost Volume Pyramid Based Depth Inference for Multi-View Stereo Jiayu | link | Northwestern Polytechnical University | 🙈 | |
CVPR2020 | Semi-Supervised Deep Learning for Monocular Depth Map Prediction | Australian National University | 🙈 |
Conference | Tittle | code | Author | mark |
---|---|---|---|---|
ECCV2014 | LSD-SLAM: Large-Scale Direct Monocular SLAM | TUM | 🙈 | |
TR2015 | ORB-SLAM: A Versatile and Accurate Monocular SLAM System | Universidad de Zaragoza | 🙈 | |
2016 | Direct Visual Odometry using Bit-Planes | Carnegie Mellon University | 🙈 | |
TR2017 | ORB-SLAM2: An Open-Source SLAM System for Monocular, Stereo, and RGB-D Cameras | Universidad de Zaragoza | 🙈 | |
2016 | A Photometrically Calibrated Benchmark For Monocular Visual Odometry | TUM | 🙈 |
Conference | Tittle | code | Author | mark |
---|---|---|---|---|
PAMI2018 | DSO: Direct Sparse Odometry | TUM | 🙈 | |
IROS2018 | LDSO: Direct Sparse Odometry with Loop Closure | TUM | 🙈 | |
ECCV2018 | Deep Virtual Stereo Odometry:Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry | TUM | 🙈 | |
2018 | Self-improving visual odometry | Magic Leap, Inc. | 🙈 |
Conference | Tittle | code | Author | mark |
---|---|---|---|---|
ICLR2019 | BA-NET: DENSE BUNDLE ADJUSTMENT NETWORKS | Simon Fraser University | 🙈 | |
TartanVO: A Generalizable Learning-based VO | link | Carnegie Mellon University | 🙈 | |
IROS | D2VO: Monocular Deep Direct Visual Odometry | 🙈 |
Conference | Tittle | code | Author | mark |
---|---|---|---|---|
ECCV2020 | Pseudo RGB-D for Self-Improving Monocular SLAM and Depth Prediction | IIIT-Delhi | 🙈 | |
CVPR2020 | VOLDOR: Visual Odometry from Log-logistic Dense Optical flow Residuals | Stevens Institute of Technology | 🙈 | |
2021 | Generalizing to the Open World: Deep Visual Odometry with Online Adaptation | Peking University | 🙈 | |
ICRA2021 | SA-LOAM: Semantic-aided LiDAR SLAM with Loop Closure | Zhejiang University | 🙈 |
Conference | Tittle | code | Author | mark |
---|---|---|---|---|
Sparse Auxiliary Networks for Unified Monocular Depth Prediction and Completion Vitor | Toyota Research Institute (TRI) | 🙈 | ||
3DV2019 | Enhancing self-supervised monocular depth estimation with traditional visual odometry | Univrses AB | 🙈 | |
ECCV2020 | S3Net: Semantic-aware self-supervised depth estimation with monocular videos and synthetic data | UCSD | 🙈 | |
CVPR2021 | AdaBins: Depth Estimation Using Adaptive Bins | Bhat | 🙈 |