In this paper, we introduce Matterport3D, a large-scale RGB-D dataset containing 10,800 panoramic views from 194,400 RGB-D images of 90 building-scale scenes. Annotations are provided with surface reconstructions, camera poses, and 2D and 3D semantic segmentations.

Request a 3D Sample Dataset Aerometrex offers a 3D reality modeling service, that is a revolutionary implementation of the “massive multi-ray matching” photogrammetric method. It offers 3D models of the highest resolution (1 inch pixel) and absolute accuracy (2 inches in X,Y & Z) derived from aerial platforms.

The dataset or its modified version cannot be redistributed without permission from dataset organizers. What's New DailyActivity3D dataset is a daily activity dataset captured by a Kinect device. There are 16 activity types: drink, eat, read book, call cellphone,write on a paper, use laptop, use vacuum cleaner, cheer up, sit still, toss paper, play game, lay down on sofa, walk, play guitar, stand up, sit down. The ObjectNet3D Dataset is available here. The Stanford Drone Dataset is available here.

VOT) Visual Tracker Benchmark (a.k.a. OTB) Object and Event Recognition. Pedestrians Daimler Pedestrian Benchmark Data Sets; CrowdHuman; 3D Objects RGB-D Object Dataset, UW; Sweet Pepper and Peduncle 3D Datasets, InKyu Sa; Places The Falling Things (FAT) dataset is a synthetic dataset for 3D object detection and pose estimation, created by NVIDIA team. It was generated by placing 3D household object models (e.g., mustard bottle, soup can, gelatin box, etc.) in virtual environments. Datasets and Benchmarks: Matterport 3D Dataset [3DV 17] Amazon Robotics Challenge 2017 Datasets [ICRA 18] SUNCG Dataset [CVPR 17] ScanNet Dataset [CVPR 17] Amazon Picking Challenge 2016 Dataset [ICRA 17] ShapeNet Dataset [ArXiv 15] SUN RGB-D Dataset [CVPR 15] RGB-D … Datasets¶.

The Campus3D provides a large-scale 3D point cloud dataset of NUS campus and a comprehensive learning benchmark for visual recognition, scene understanding and varies kinds of vision problems.

3D Model/Shape Retrieval Datasets. ShapeNet Dataset. The ShapeNetCore covers 55 common object categories with about 51,300 unique 3D models.

The ObjectNet3D Dataset is available here. The Stanford Drone Dataset is available here. The Stanford Large-Scale Indoor Spaces 3D dataset is available here. The Multiview Tracking dataset is available here.

Licenser: Atribución-NoComercial 4.0 Internacional (CC BY-NC 4.0) Taggar: PRESUPUESTO PERSONAL. Filtrera resultat 1 dataset hittades. Taggar: Fully Assembled Right-Hand Drive Ministry of Trade and Industry. Filtrera resultat.

MuPoTs-3D (Multi-person Pose estimation Test Set in 3D) is a dataset for pose estimation composed of more than 8,000 frames from 20 real-world scenes with up to three subjects. The poses are annotated with a 14-point skeleton model. Source: DOPE: Distillation Of Part Experts for whole-body 3D pose estimation in the wild For the images always the license of the original dataset applies, we only provide our cut-outs for convenience and reproducibility. The datasets are linked from their respective thumbnail image.
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Annotations are provided with surface reconstructions, camera poses, and 2D and 3D semantic segmentations. We have created a dataset of more than ten thousand 3D scans of real objects. To create the dataset, we recruited 70 operators, equipped them with consumer-grade mobile 3D scanning setups, and paid them to scan objects in their environments. This dataset contains aligned image and range data: Make3D Image and Laser Depthmap Image and Laser and Stereo Image and 1D Laser Image and Depth for Objects Video and Depth (coming soon) Different types of examples are there---outdoor scenes (about 1000), indoor (about 50), synthetic objects (about 7000), etc.

This dataset contains 10,800 aligned 3D panoramic views (RGB + depth per pixel) from 194,400 RGB + depth images of 90 building-scale scenes. All of these scenes were captured with Matterport’s Pro 3D Camera. The 3D models of the scenes have been hand-labeled with instance-level object segmentation.
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KTH-3D-TOTAL: A 3D Dataset for Discovering Spatial Structures for Long-Term Autonomous Learning. Akshaya Thippur, Rares Ambrus, Gaurav Agrawal, Adria

cereales de invierno 2020. Du kan också av A Malehmir · 2020 — presenterar sin masteruppsats "2D Reflection Imaging of Sparse 3D reflection seismic profiles were extracted from a sparse 3D dataset in 2 197 dataset hittades · VHI - 2016/09/13.

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Jun 27, 2020 This dataset extends the Urban Semantic 3D (US3D) dataset developed and first released for the 2019 IEEE GRSS Data Fusion Contest

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A3D dataset is a frontal-view dataset which consists of both day and night-time data with 3D annotations, unlike KITTI, H3D (only day-time data), and KAIST (only 2D). There are major differences in driving and annotation planning between A3D and nuScenes datasets, as shown in TableI. First, the nuScenes data is collected from a very small part

Using only the existing 3D pose data and 2D pose data, we show state-of-the-art performances on established benchmarks through transfer of learned features, while also 3D Garment Datasets. While most of existing repositories focus on naked [6,8, 39,9] or clothed [68] human body, datasets specially tailored for 3D garment is very limited. BUFF dataset [67] consists of high-resolution 4D scans of clothed human with very limited ammount. In addition, it fails to provide separated models for body and clothing. We fill this gap with RELLIS-3D, a multimodal dataset collected in an off-road environment containing annotations for 13,556 LiDAR scans and 6,235 images. The data was collected on the Rellis Campus of Texas A\&M University and presents challenges to existing algorithms related to class imbalance and environmental topography. Cityscapes 3D Dataset Released.

Dataset Size Currently, 65 sequences (5.5 hours) and 1.5 millions of 3D skeletons are available.