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Depth Completion datasets

archive 2025-07-28

11 datasets carry the task tag "Depth Completion" (the task itself: Depth Completion), ordered by the archive's paper count. Page 1 of 1: 11 shown of 11. Facet routes are this site's own (the archive records the tag string, not a page).

The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.

Filter 51 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets

All 12,172 Question Answering 413Semantic Segmentation 347Object Detection 332Image Classification 283Classification 222Text Classification 167Language Modelling 166Text Generation 162Visual Question Answering (VQA) 144Named Entity Recognition (NER) 130Pose Estimation 124Anomaly Detection 119Action Recognition 115Instance Segmentation 111Sentiment Analysis 104Text Summarization 98Domain Adaptation 96Speech Recognition 96Reading Comprehension 95Information Retrieval 932D Object Detection 92Image Retrieval 87Machine Translation 82Relation Extraction 822D Semantic Segmentation 81Natural Language Inference 81Image Captioning 79Image Generation 79Depth Estimation 77Node Classification 75Natural Language Understanding 72Autonomous Driving 70Code Generation 70Object Tracking 693D Object Detection 67Face Recognition 67Link Prediction 67Person Re-Identification 65Data Augmentation 63Multi-Task Learning 593D Reconstruction 58Common Sense Reasoning 56Recommendation Systems 56Video Understanding 56Optical Character Recognition (OCR) 55Graph Classification 54Abstractive Text Summarization 52Emotion Recognition 52Medical Image Segmentation 52Word Embeddings 52Depth Completion 11

Depth Completion datasets 1–11 of 11

KITTI
KITTI (Karlsruhe Institute of Technology and Toyota Technological Institute) is one of the most popular datasets for use in mobile robotics and autonomous driving.
ImagesLiDARObject DetectionSemantic SegmentationPose EstimationObject Tracking3D Object DetectionImage Super-Resolution+41 tasks
3,661 papers · 137 benchmarks
NYUv2 (NYU-Depth V2)
The NYU-Depth V2 data set is comprised of video sequences from a variety of indoor scenes as recorded by both the RGB and Depth cameras from the Microsoft Kinect.
RGB-DSemantic SegmentationInstance Segmentation3D Object DetectionDepth EstimationPanoptic SegmentationMonocular Depth Estimation+12 tasks
986 papers · 16 benchmarks
Matterport3D
The Matterport3D dataset is a large RGB-D dataset for scene understanding in indoor environments.
3DRGB-DSemantic SegmentationDepth EstimationMonocular Depth EstimationDepth CompletionDepth Prediction
461 papers · 4 benchmarks
VOID (Visual Odometry with Inertial and Depth)
The dataset was collected using the Intel RealSense D435i camera, which was configured to produce synchronized accelerometer and gyroscope measurements at 400 Hz, along with synchronized VGA-size (640 x 480) RGB and depth streams at 30 Hz.
ImagesPoint cloudRGB-DRGB VideoDepth EstimationDepth Completion
26 papers · 1 benchmark
KITTI-Depth
The KITTI-Depth dataset includes depth maps from projected LiDAR point clouds that were matched against the depth estimation from the stereo cameras.
ImagesPoint cloudDepth EstimationAutonomous DrivingDepth Completion
14 papers · 0 benchmarks
TransCG
TransCG is the first large-scale real-world dataset for transparent object depth completion and grasping, which contains 57,715 RGB-D images of 51 transparent objects and many opaque objects captured from different perspectives (~240…
RGB-DDepth CompletionTransparent Object Depth Estimation
7 papers · 1 benchmark
SuperCaustics
SuperCaustics is a simulation tool made in Unreal Engine for generating massive computer vision datasets that include transparent objects.
ImagesInteractiveEnvironmentRGB-DRGB VideoLiDARPhysicsDepth EstimationDepth CompletionSurface Normals EstimationTransparent Object Depth EstimationCaustics SegmentationTransparent Object Detection
2 papers · 0 benchmarks
BIDCD (Bosch Industrial Depth Completion Dataset)
Bosch Industrial Depth Completion Dataset (BIDCD) is an RGBD dataset for of static table-top scenes with industrial objects.
ImagesRGB-DDepth Completion
1 paper · 0 benchmarks
ConSLAM (Construction Dataset for SLAM)
ConSLAM is a real-world dataset collected periodically on a construction site to measure the accuracy of mobile scanners' SLAM algorithms.
Videos3DPoint cloudTrackingRGB VideoLiDARPose EstimationDepth EstimationPose TrackingCamera Localization2D Pose EstimationVisual Odometry+12 tasks
1 paper · 0 benchmarks
PLAD (Point Line and Depth dataset)
PLAD is a dataset where sparse depth is provided by line-based visual SLAM to verify StructMDC.
Images3d meshesRGB-DDepth Completion
1 paper · 1 benchmark
Multi-Spectral Stereo Dataset (RGB, NIR, thermal images, LiDAR, GPS/IMU)
Abstract: We introduce the multi-spectral stereo (MS2) outdoor dataset, including stereo RGB, stereo NIR, stereo thermal, stereo LiDAR data, and GPS/IMU information.
ImagesPoint cloudStereoLiDARDepth EstimationVisual OdometryDepth CompletionThermal Image SegmentationStereo Depth EstimationDepth Prediction
0 papers · 0 benchmarks

Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.