SOTAVerified

Depth Completion

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

Papers

Showing 201225 of 242 papers

TitleStatusHype
Uncertainty depth estimation with gated images for 3D reconstruction0
Depth Completion Using a View-constrained Deep Prior0
FIS-Nets: Full-image Supervised Networks for Monocular Depth Estimation0
Don't Forget The Past: Recurrent Depth Estimation from Monocular Video0
Depth Completion via Deep Basis Fitting0
CSPN++: Learning Context and Resource Aware Convolutional Spatial Propagation Networks for Depth Completion0
Depth Completion from Sparse LiDAR Data with Depth-Normal Constraints0
ClearGrasp: 3D Shape Estimation of Transparent Objects for ManipulationCode0
Indoor Depth Completion with Boundary Consistency and Self-AttentionCode0
To complete or to estimate, that is the question: A Multi-Task Approach to Depth Completion and Monocular Depth Estimation0
Image-Guided Depth Sampling and Reconstruction0
Learning Guided Convolutional Network for Depth CompletionCode0
Conf-Net: Toward High-Confidence Dense 3D Point-Cloud with Error-Map PredictionCode0
Improving 3D Object Detection for Pedestrians with Virtual Multi-View Synthesis Orientation Estimation0
S&CNet: Monocular Depth Completion for Autonomous Systems and 3D Reconstruction0
Deep RGB-D Canonical Correlation Analysis For Sparse Depth CompletionCode0
Generating and Exploiting Probabilistic Monocular Depth EstimatesCode0
Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer VisionCode0
Veritatem Dies Aperit - Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding ApproachCode0
Unsupervised Depth Completion from Visual Inertial OdometryCode0
Noise-Aware Unsupervised Deep Lidar-Stereo FusionCode0
3D LiDAR and Stereo Fusion using Stereo Matching Network with Conditional Cost Volume NormalizationCode0
Veritatem Dies Aperit- Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding ApproachCode0
DFineNet: Ego-Motion Estimation and Depth Refinement from Sparse, Noisy Depth Input with RGB Guidance0
Depth Coefficients for Depth Completion0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SparseConvsRMSE1,601Unverified
2NConv-CNNRMSE1,268Unverified
3VOICEDRMSE1,169.97Unverified
4ScaffNet-FusionNetRMSE1,121.93Unverified
5KBNetRMSE1,069.47Unverified
6Spade-sDRMSE1,035Unverified
7HMS-NetRMSE937Unverified
8Spade-RGBsDRMSE918Unverified
9NConv-CNN-L1RMSE859Unverified
10NConv-CNN-L2RMSE830Unverified
#ModelMetricClaimedVerifiedStatus
1SS-S2DMAE178.85Unverified
2DDPMAE151.86Unverified
3VOICEDMAE85.05Unverified
4ScaffNet-FusionNetMAE59.53Unverified
5KBNetMAE39.8Unverified
6NLSPNMAE26.74Unverified
#ModelMetricClaimedVerifiedStatus
1Struct-MDCRMSE0.14Unverified
2DSNRMSE0.1Unverified
3NLSPNRMSE0.09Unverified
#ModelMetricClaimedVerifiedStatus
1SA+SSIM+BCRMSE1.09Unverified
2DM-LRN-b4RMSE1Unverified
#ModelMetricClaimedVerifiedStatus
1FusionDepthRMSE1,193.92Unverified
#ModelMetricClaimedVerifiedStatus
1CFCNetRMSE 2.96Unverified
#ModelMetricClaimedVerifiedStatus
1DSNREL0.02Unverified
#ModelMetricClaimedVerifiedStatus
1Struct-MDCMAE1,170.3Unverified
#ModelMetricClaimedVerifiedStatus
1Struct-MDCMAE111.33Unverified