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 76100 of 242 papers

TitleStatusHype
Propagating Confidences through CNNs for Sparse Data RegressionCode0
Radar-Camera Pixel Depth Association for Depth CompletionCode0
Sparse and noisy LiDAR completion with RGB guidance and uncertaintyCode0
Multi-Modal Masked Pre-Training for Monocular Panoramic Depth CompletionCode0
AugUndo: Scaling Up Augmentations for Monocular Depth Completion and EstimationCode0
DFuseNet: Deep Fusion of RGB and Sparse Depth Information for Image Guided Dense Depth CompletionCode0
MIPI 2022 Challenge on RGB+ToF Depth Completion: Dataset and ReportCode0
Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer VisionCode0
3D LiDAR and Stereo Fusion using Stereo Matching Network with Conditional Cost Volume NormalizationCode0
FCDSN-DC: An Accurate and Lightweight Convolutional Neural Network for Stereo Estimation with Depth CompletionCode0
Prior based Sampling for Adaptive LiDARCode0
NeSLAM: Neural Implicit Mapping and Self-Supervised Feature Tracking With Depth Completion and DenoisingCode0
Conf-Net: Toward High-Confidence Dense 3D Point-Cloud with Error-Map PredictionCode0
Adaptive LiDAR Sampling and Depth Completion using Ensemble VarianceCode0
Masked Spatial Propagation Network for Sparsity-Adaptive Depth RefinementCode0
Confidence Propagation through CNNs for Guided Sparse Depth RegressionCode0
DepthNet: Real-Time LiDAR Point Cloud Depth Completion for Autonomous VehiclesCode0
Unsupervised Depth Completion from Visual Inertial OdometryCode0
Learning Depth with Convolutional Spatial Propagation NetworkCode0
Indoor Depth Completion with Boundary Consistency and Self-AttentionCode0
In Defense of Classical Image Processing: Fast Depth Completion on the CPUCode0
Learning Guided Convolutional Network for Depth CompletionCode0
Noise-Aware Unsupervised Deep Lidar-Stereo FusionCode0
Sparse and noisy LiDAR completion with RGB guidance anduncertaintyCode0
Depth Completion via Deep Basis Fitting0
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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