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Depth Completion

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평가표: 9
보존된 평가 기록: 32

The Depth Completion task is a sub-problem of depth estimation. In the sparse-to-dense depth completion problem, one wants to infer the dense depth map of a 3-D scene given an RGB image and its corresponding sparse reconstruction in the form of a sparse depth map obtained either from computational methods such as SfM (Strcuture-from-Motion) or active sensors such as lidar or structured light sensors.

Source: LiStereo: Generate Dense Depth Maps from LIDAR and Stereo Imagery , Unsupervised Depth Completion from Visual Inertial Odometry

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/AutoAILab/FusionDepth

공식 코드

Advancing Self-supervised Monocular Depth Learning with Sparse LiDAR

https://github.com/DTU-PAS/steered-marigold

공식 코드

SteeredMarigold: Steering Diffusion Towards Depth Completion of Largely Incomplete Depth Maps

https://github.com/F-Barto/LiDARTouch

공식 코드

LiDARTouch: Monocular metric depth estimation with a few-beam LiDAR

https://github.com/FlorisE/neural-labeling

공식 코드

NeuralLabeling: A versatile toolset for labeling vision datasets using Neural Radiance Fields

https://github.com/JUGGHM/PENet_ICRA2021

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PENet: Towards Precise and Efficient Image Guided Depth Completion

https://github.com/KochPJ/vanishing-depth

공식 코드

Vanishing Depth: A Depth Adapter with Positional Depth Encoding for Generalized Image Encoders

https://github.com/LittlePey/SFD

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Sparse Fuse Dense: Towards High Quality 3D Detection with Depth Completion

https://github.com/MMehdiMousavi/SuperCaustics

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SuperCaustics: Real-time, open-source simulation of transparent objects for deep learning applications

https://github.com/NVlabs/implicit_depth

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RGB-D Local Implicit Function for Depth Completion of Transparent Objects

https://github.com/Shreeyak/cleargrasp

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ClearGrasp: 3D Shape Estimation of Transparent Objects for Manipulation

https://github.com/ShreyasSkandanS/DFuseNet

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DFuseNet: Deep Fusion of RGB and Sparse Depth Information for Image Guided Dense Depth Completion

https://github.com/Wang-xjtu/PacGDC

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PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency

https://github.com/Wang-xjtu/SPNet

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Scale Propagation Network for Generalizable Depth Completion

https://github.com/Wenchao-Du/GAENet

공식 코드

Depth Completion using Geometry-Aware Embedding

https://github.com/XinJCheng/CSPN

공식 코드

Learning Depth with Convolutional Spatial Propagation Network

https://github.com/XuelianCheng/LidarStereoNet

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Noise-Aware Unsupervised Deep Lidar-Stereo Fusion

https://github.com/abdo-eldesokey/nconv

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Confidence Propagation through CNNs for Guided Sparse Depth Regression

https://github.com/abdo-eldesokey/pncnn

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Uncertainty-Aware CNNs for Depth Completion: Uncertainty from Beginning to End

https://github.com/alexklwong/adaframe-depth-completion

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An Adaptive Framework for Learning Unsupervised Depth Completion

https://github.com/alexklwong/calibrated-backprojection-network

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Unsupervised Depth Completion with Calibrated Backprojection Layers

https://github.com/alexklwong/learning-topology-synthetic-data

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Learning Topology from Synthetic Data for Unsupervised Depth Completion

https://github.com/alexklwong/mondi-python

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Monitored Distillation for Positive Congruent Depth Completion

https://github.com/alexklwong/unsupervised-depth-completion-visual-inertial-odometry

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Unsupervised Depth Completion from Visual Inertial Odometry

https://github.com/alexsunnik/redc

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Revisiting Deformable Convolution for Depth Completion

https://github.com/alexsunnik/revisiting-deformable-convolution-for-depth-completion

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Revisiting Deformable Convolution for Depth Completion

https://github.com/amitshomer/sampledepth

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Prior based Sampling for Adaptive LiDAR

https://github.com/anonymoustbd/mmmpt

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Multi-Modal Masked Pre-Training for Monocular Panoramic Depth Completion

https://github.com/atapour/temporal-depth-segmentation

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Veritatem Dies Aperit- Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding Approach

https://github.com/barbararoessle/dense_depth_priors_nerf

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Dense Depth Priors for Neural Radiance Fields from Sparse Input Views

https://github.com/bartn8/vppdc

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Revisiting Depth Completion from a Stereo Matching Perspective for Cross-domain Generalization

https://github.com/choyingw/CFCNet

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Deep RGB-D Canonical Correlation Analysis For Sparse Depth Completion

https://github.com/choyingw/SCADC-DepthCompletion

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Scene Completeness-Aware Lidar Depth Completion for Driving Scenario

https://github.com/danishnazir/SemAttNet

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SemAttNet: Towards Attention-based Semantic Aware Guided Depth Completion

https://github.com/denyingmxd/cfpnet

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CFPNet: Improving Lightweight ToF Depth Completion via Cross-zone Feature Propagation

https://github.com/dtc111111/neslam

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NeSLAM: Neural Implicit Mapping and Self-Supervised Feature Tracking With Depth Completion and Denoising

https://github.com/dwhou/emdc-pytorch

공식 코드

Learning an Efficient Multimodal Depth Completion Model

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