Self-Supervised depth kalilia

Related tags

Deep LearningSelf-Supervised-depth
Overview

Self-Supervised-depth

by kalilia.

Contents

0-depth-estimation-overview

Conference Tittle code Author mark note
Single Image Depth Estimation: An Overview Istanbul Technical University πŸ™‰

*-datasets

Tittle yaer mark note
Vision meets Robotics: The KITTI Dataset 2012 Karlsruhe Institute of Technology
nuScenes: A multimodal dataset for autonomous driving 2018 nuTonomy: an APTIV company

1-Monocular-depth with Cost Volume

Conference Tittle code Author mark note
NIPS2020 Forget About the LiDAR: Self-Supervised Depth Estimators with MED Probability Volumes Korea Advanced Institute of Science and Technology πŸ™‰ link
CVPR2021 DRO: Deep Recurrent Optimizer for Structure-from-Motion Alibaba A.I. Labs πŸ™ˆ link
CVPR2021 The Temporal Opportunist: Self-Supervised Multi-Frame Monocular Depth link Niantic πŸ™ˆ
CVPR2020 Self-supervised Monocular Trained Depth Estimation using Self-attention and Discrete Disparity Volume link Australian Institute for Machine Learning πŸ™ˆ
ECCV2020 Feature-metric Loss for Self-supervised Learning of Depth and Egomotion link πŸ™ˆ

2-Mono-SfM

2017

Conference Tittle code Author mark note
CVPR2017 Semi-Supervised Deep Learning for Monocular Depth Map Prediction RWTH Aachen University πŸ™ˆ
CVPR2017 SfMLearner: Unsupervised Learning of Depth and Ego-Motion from Video link UC Berkeley ⭐ link

2018

Conference Tittle code Author mark note
CVPR2018 DVO: Learning Depth from Monocular Videos using Direct Methods Carnegie Mellon University πŸ™ˆ
CVPR2018 GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose link SenseTime Research πŸ™ˆ
ECCV2018 DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Task Consistency ) Virginia Tech πŸ™ˆ
ECCV2018 Supervising the new with the old: learning SFM from SFM ) University of Oxford πŸ™ˆ

2019

Conference Tittle code Author mark note
2019 Self-Supervised 3D Keypoint Learning for Ego-motion Estimation Toyota Research Institute (TRI) πŸ™ˆ
ICRA2019 SuperDepth: Self-Supervised, Super-Resolved Monocular Depth Estimation Toyota Research Institute (TRI) πŸ™ˆ
AAAI2019 Depth prediction without the sensors: Leveraging structure for unsupervised learning from monocular videos Harvard University/Google Brain πŸ™ˆ
ICCV2019 Unsupervised High-Resolution Depth Learning From Videos With Dual Networks Tsinghua University πŸ™ˆ
ICCV2019 Self-Supervised Monocular Depth Hints link Niantic πŸ™ˆ
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 πŸ™ˆ
CVPR2019 Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion Segmentation Max Planck Institute for Intelligent Systems πŸ™ˆ
CoRL2019 Robust Semi-Supervised Monocular Depth Estimation with Reprojected Distances Toyota Research Institute (TRI) πŸ™ˆ

2020

Conference Tittle code Author mark note
ECCV2020 DeepSFM: Structure From Motion Via Deep Bundle Adjustment Fudan University πŸ™ˆ
CoRL2020 Unsupervised Monocular Depth Learning in Dynamic Scenes Google Research πŸ™ˆ
CoRL2020 Attentional Separation-and-Aggregation Network for Self-supervised Depth-Pose Learning in Dynamic Scenes Tsinghua University πŸ™‰
3DV2020 Neural Ray Surfaces for Self-Supervised Learning of Depth and Ego-motion Toyota Research Institute (TRI)
ICLR2020 Semantically-Guided Representation Learning for Self-Supervised Monocular Depth Toyota Research Institute (TRI)
CVPR2020 On the uncertainty of self-supervised monocular depth estimation link University of Bologna, Italy πŸ™ˆ
CVPR2020 Towards Better Generalization: Joint Depth-Pose Learning without PoseNet link Tsinghua University πŸ™ˆ link
CVPR2020 3D Packing for Self-Supervised Monocular Depth Estimation Toyota Research Institute (TRI) 🌟 link
CVPR2020 Self-supervised monocular trained depth estimation using self-attention and discrete disparity volume University of Adelaide πŸ™ˆ
2020 SAFENet: Self-Supervised Monocular Depth Estimation with Semantic-Aware Feature Extraction link Toyota Research Institute (TRI) πŸ™ˆ
2020 Self-Supervised Monocular Depth Estimation : Solving the Dynamic Object Problem by Semantic Guidance Technische UniversitΒ¨at Braunschweig, Germany πŸ™ˆ
IROS2020 Toward Hierarchical Self-Supervised Monocular Absolute Depth Estimation for Autonomous Driving Applications link Tongji University πŸ™ˆ

2021

Conference Tittle code Author mark note
AAAI2021 HR-Depth : High Resolution Self-Supervised Monocular Depth Estimation link Zhejiang University ⭐ link
AAAI2021 Learning Monocular Depth in Dynamic Scenes via Instance-Aware Projection Consistency KAIST ⭐ link
CVPR2021 Manydepth:The Temporal Opportunist: Self-Supervised Multi-Frame Monocular Depth link Niantic πŸ™ˆ
CVPR2021 MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera link TUM πŸ™ˆ
IROS2021 Self-Supervised Scale Recovery for Monocular Depth and Egomotion Estimation University of Toronto πŸ™ˆ
2021 Self-supervised Depth Estimation Leveraging Global Perception and Geometric Smoothness Using On-board Videos Hong Kong Polytechnic University πŸ™ˆ
2021 Self-Supervised Structure-from-Motion through Tightly-Coupled Depth and Egomotion Networks University of Toronto πŸ™ˆ
2021 Moving SLAM: Fully Unsupervised Deep Learning in Non-Rigid Scenes HKUST πŸ™ˆ
2021 Unsupervised Joint Learning of Depth, Optical Flow, Ego-motion from Video Tongji University πŸ™ˆ
2021 Monocular Depth Estimation through Virtual-world Supervision and Real-world SfM Self-Supervision πŸ™ˆ
2021 Self-Supervised Learning of Depth and Ego- Motion from Video by Alternative Training and Geometric Constraints from 3D to 2D πŸ™ˆ
-update-time-09-13-2021-
ICCV2021 Fine-grained Semantics-aware Representation Enhancement for Self-supervised Monocular Depth Estimation Seoul National University πŸ™ˆ
ICCV2021 Regularizing Nighttime Weirdness: Efficient Self-supervised Monocular Depth Estimation in the Dark Nanjing University of Science and Technology πŸ™ˆ
ICCV2021 Self-supervised Monocular Depth Estimation for All Day Images using Domain Separation Zhejiang University πŸ™ˆ
ICCV2021 StructDepth: Leveraging the structural regularities for self-supervised indoor depth estimation Shanghai Jiao Tong University πŸ™ˆ
ICCV2021 MonoIndoor: Towards Good Practice of Self-Supervised Monocular Depth Estimation for Indoor Environments OPPO US Research Center πŸ™ˆ
Sensors Journal 2021 Unsupervised Monocular Depth Perception: Focusing on Moving Objects Chinese University of Hong Kong πŸ™ˆ
2021 R4Dyn: Exploring Radar for Self-Supervised Monocular Depth Estimation of Dynamic Scenes TUM ⭐
2021 Unsupervised Monocular Depth Estimation in Highly Complex Environments East China University of Science and Technology πŸ™ˆ

3-Multi-view-stereo

Conference Tittle code Author mark
PAMI2008 SGM：Stereo processing by Semi-Global matching and Mutual Information German Aerospace Cente πŸ™ˆ
ECCV2016 Unsupervised CNN for Single View Depth Estimation: Geometry to the Rescue University of Adelaide πŸ™ˆ
CVPR2017 DispNet: Unsupervised Monocular Depth Estimation with Left-Right Consistency University College London πŸ™ˆ
Cost Volume Pyramid Based Depth Inference for Multi-View Stereo Jiayu link Northwestern Polytechnical University πŸ™ˆ
CVPR2020 Semi-Supervised Deep Learning for Monocular Depth Map Prediction Australian National University πŸ™ˆ
AAAI2021 Self-supervised Multi-view Stereo via Effective Co-Segmentation and Data-Augmentation South China University of Technology πŸ™ˆ
CVPR2021 Differentiable Diffusion for Dense Depth Estimation from Multi-view Images Brown University πŸ™ˆ
ICCV2021 NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo Australian National University ⭐

4-SLAM-Visual-Odometry

Conference Tittle code Author mark
ECCV2014 LSD-SLAM: Large-Scale Direct Monocular SLAM TUM πŸ™ˆ
TR2015 ORB-SLAM: A Versatile and Accurate Monocular SLAM System Universidad de Zaragoza πŸ™ˆ
2016 Direct Visual Odometry using Bit-Planes Carnegie Mellon University πŸ™ˆ
TR2017 ORB-SLAM2: An Open-Source SLAM System for Monocular, Stereo, and RGB-D Cameras Universidad de Zaragoza πŸ™ˆ
2016 A Photometrically Calibrated Benchmark For Monocular Visual Odometry TUM πŸ™ˆ

2018

Conference Tittle code Author mark
PAMI2018 DSO: Direct Sparse Odometry TUM πŸ™ˆ
IROS2018 LDSO: Direct Sparse Odometry with Loop Closure TUM πŸ™ˆ
ECCV2018 Deep Virtual Stereo Odometry:Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry TUM πŸ™ˆ
2018 Self-improving visual odometry Magic Leap, Inc. πŸ™ˆ

2019

Conference Tittle code Author mark
ICLR2019 BA-NET: DENSE BUNDLE ADJUSTMENT NETWORKS Simon Fraser University πŸ™ˆ
TartanVO: A Generalizable Learning-based VO link Carnegie Mellon University πŸ™ˆ
IROS D2VO: Monocular Deep Direct Visual Odometry πŸ™ˆ

2020

Conference Tittle code Author mark
ECCV2020 Pseudo RGB-D for Self-Improving Monocular SLAM and Depth Prediction IIIT-Delhi πŸ™ˆ
CVPR2020 VOLDOR: Visual Odometry from Log-logistic Dense Optical flow Residuals Stevens Institute of Technology πŸ™ˆ
2021 Generalizing to the Open World: Deep Visual Odometry with Online Adaptation Peking University πŸ™ˆ
ICRA2021 SA-LOAM: Semantic-aided LiDAR SLAM with Loop Closure Zhejiang University πŸ™ˆ

Light-Filed-based-depth

Conference Tittle code Author mark
TPAMI2021 Revisiting Light Field Rendering with Deep Anti-Aliasing Neural Network Northeastern University πŸ™ˆ
CVPR2021 Differentiable Diffusion for Dense Depth Estimation from Multi-view Images Brown University πŸ™ˆ
IROS2021 Unsupervised Learning of Depth Estimation and Visual Odometry for Sparse Light Field Cameras Brown University πŸ™ˆ
2021 Occlusion-aware Unsupervised Learning of Depth from 4-D Light Fields University of Sydney πŸ™ˆ

6-depth-estimation-and-complementation

Conference Tittle code Author mark
Sparse Auxiliary Networks for Unified Monocular Depth Prediction and Completion Vitor Toyota Research Institute (TRI) πŸ™ˆ
3DV2019 Enhancing self-supervised monocular depth estimation with traditional visual odometry Univrses AB πŸ™ˆ
ECCV2020 S3Net: Semantic-aware self-supervised depth estimation with monocular videos and synthetic data UCSD πŸ™ˆ
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