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
RDFC-GAN: RGB-Depth Fusion CycleGAN for Indoor Depth Completion0
RGB-Depth Fusion GAN for Indoor Depth Completion0
RGB Guided ToF Imaging System: A Survey of Deep Learning-based Methods0
RigNet++: Semantic Assisted Repetitive Image Guided Network for Depth Completion0
Radar-Camera Pixel Depth Association for Depth CompletionCode0
Veritatem Dies Aperit- Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding ApproachCode0
Propagating Confidences through CNNs for Sparse Data RegressionCode0
Progressive Depth Decoupling and Modulating for Flexible Depth CompletionCode0
Conf-Net: Toward High-Confidence Dense 3D Point-Cloud with Error-Map PredictionCode0
Prior based Sampling for Adaptive LiDARCode0
In Defense of Classical Image Processing: Fast Depth Completion on the CPUCode0
Sparsity Invariant CNNsCode0
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
Generating and Exploiting Probabilistic Monocular Depth EstimatesCode0
Parse Geometry from a Line: Monocular Depth Estimation with Partial Laser ObservationCode0
FCDSN-DC: An Accurate and Lightweight Convolutional Neural Network for Stereo Estimation with Depth CompletionCode0
Noise-Aware Unsupervised Deep Lidar-Stereo FusionCode0
NeSLAM: Neural Implicit Mapping and Self-Supervised Feature Tracking With Depth Completion and DenoisingCode0
Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer VisionCode0
SDformer: Efficient End-to-End Transformer for Depth CompletionCode0
What You See Is What You Detect: Towards better Object Densification in 3D detectionCode0
DFuseNet: Deep Fusion of RGB and Sparse Depth Information for Image Guided Dense Depth CompletionCode0
Confidence Propagation through CNNs for Guided Sparse Depth RegressionCode0
DepthNet: Real-Time LiDAR Point Cloud Depth Completion for Autonomous VehiclesCode0
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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