Self-Supervised depth kalilia

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
Code for the TIP 2021 Paper "Salient Object Detection with Purificatory Mechanism and Structural Similarity Loss"

PurNet Project for the TIP 2021 Paper "Salient Object Detection with Purificatory Mechanism and Structural Similarity Loss" Abstract Image-based salie

Jinming Su 4 Aug 25, 2022
Tutorials and implementations for "Self-normalizing networks"

Self-Normalizing Networks Tutorials and implementations for "Self-normalizing networks"(SNNs) as suggested by Klambauer et al. (arXiv pre-print). Vers

Institute of Bioinformatics, Johannes Kepler University Linz 1.6k Jan 07, 2023
gitγ€ŠPseudo-ISP: Learning Pseudo In-camera Signal Processing Pipeline from A Color Image Denoiser》(2021) GitHub: [fig5]

Pseudo-ISP: Learning Pseudo In-camera Signal Processing Pipeline from A Color Image Denoiser Abstract The success of deep denoisers on real-world colo

Yue Cao 51 Nov 22, 2022
A transformer-based method for Healthcare Image Captioning in Vietnamese

vieCap4H Challenge 2021: A transformer-based method for Healthcare Image Captioning in Vietnamese This repo GitHub contains our solution for vieCap4H

Doanh B C 4 May 05, 2022
Code repository for Semantic Terrain Classification for Off-Road Autonomous Driving

BEVNet Datasets Datasets should be put inside data/. For example, data/semantic_kitti_4class_100x100. Training BEVNet-S Example: cd experiments bash t

(Brian) JoonHo Lee 24 Dec 12, 2022
Spatial-Location-Constraint-Prototype-Loss-for-Open-Set-Recognition

Spatial Location Constraint Prototype Loss for Open Set Recognition Official PyTorch implementation of "Spatial Location Constraint Prototype Loss for

Xia Ziheng 12 Jun 24, 2022
AirCode: A Robust Object Encoding Method

AirCode This repo contains source codes for the arXiv preprint "AirCode: A Robust Object Encoding Method" Demo Object matching comparison when the obj

Chen Wang 30 Dec 09, 2022
Official and maintained implementation of the paper "OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data" [BMVC 2021].

OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data Christoph Reich, Tim Prangemeier, Γ–zdemir Cetin & Heinz Koeppl | Pr

Christoph Reich 23 Sep 21, 2022
Accelerated Multi-Modal MR Imaging with Transformers

Accelerated Multi-Modal MR Imaging with Transformers Dependencies numpy==1.18.5 scikit_image==0.16.2 torchvision==0.8.1 torch==1.7.0 runstats==1.8.0 p

54 Dec 16, 2022
Process text, including tokenizing and representing sentences as vectors and Applying some concepts like RNN, LSTM and GRU to create a classifier can detect the language in which a sentence is written from among 17 languages.

Language Identifier What is this ? The goal of this project is to create a model that is able to predict a given sentence language through text proces

Hossam Asaad 9 Dec 15, 2022
Lucid library adapted for PyTorch

Lucent PyTorch + Lucid = Lucent The wonderful Lucid library adapted for the wonderful PyTorch! Lucent is not affiliated with Lucid or OpenAI's Clarity

Lim Swee Kiat 520 Dec 26, 2022
This solves the autonomous driving issue which is supported by deep learning technology. Given a video, it splits into images and predicts the angle of turning for each frame.

Self Driving Car An autonomous car (also known as a driverless car, self-driving car, and robotic car) is a vehicle that is capable of sensing its env

Sagor Saha 4 Sep 04, 2021
Romanian Automatic Speech Recognition from the ROBIN project

RobinASR This repository contains Robin's Automatic Speech Recognition (RobinASR) for the Romanian language based on the DeepSpeech2 architecture, tog

RACAI 10 Jan 01, 2023
[NeurIPS 2021] "Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks" by Yonggan Fu, Qixuan Yu, Yang Zhang, Shang Wu, Xu Ouyang, David Cox, Yingyan Lin

Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks Yonggan Fu, Qixuan Yu, Yang Zhang, S

12 Dec 11, 2022
Deep Reinforcement Learning based Trading Agent for Bitcoin

Deep Trading Agent Deep Reinforcement Learning based Trading Agent for Bitcoin using DeepSense Network for Q function approximation. For complete deta

Kartikay Garg 669 Dec 29, 2022
Library for time-series-forecasting-as-a-service.

TIMEX TIMEX (referred in code as timexseries) is a framework for time-series-forecasting-as-a-service. Its main goal is to provide a simple and generi

Alessandro Falcetta 8 Jan 06, 2023
A Fast and Stable GAN for Small and High Resolution Imagesets - pytorch

A Fast and Stable GAN for Small and High Resolution Imagesets - pytorch The official pytorch implementation of the paper "Towards Faster and Stabilize

Bingchen Liu 455 Jan 08, 2023
Open-source code for Generic Grouping Network (GGN, CVPR 2022)

Open-World Instance Segmentation: Exploiting Pseudo Ground Truth From Learned Pairwise Affinity Pytorch implementation for "Open-World Instance Segmen

Meta Research 99 Dec 06, 2022
FluxTraining.jl gives you an endlessly extensible training loop for deep learning

A flexible neural net training library inspired by fast.ai

86 Dec 31, 2022
Summary Explorer is a tool to visually explore the state-of-the-art in text summarization.

Summary Explorer Summary Explorer is a tool to visually inspect the summaries from several state-of-the-art neural summarization models across multipl

Webis 42 Aug 14, 2022