4 cloud categories (cloud, thin cloud, cloud shadows, clear), 96 Landsat 8 scenes (30m res. 20k 256 x 256 pixel chips, 2 categories oil-palm and other, annotator confidence score. road-flooded, ). 2020, xView 2018 Detection Challenge (DIUx, Jul 2018) 550k building footprints & 4 damage scale categories, 20 global locations and 7 disaster types (wildfire, landslides, dam collapses, volcanic eruptions, earthquakes/tsunamis, wind, flooding), Worldview-3 imagery (0.3m res. Slovenia Land Cover Classification (Sinergise, Feb 2019) 6 urban land cover classes, raster mask labels, 4-band RGB-IR aerial imagery (0.05m res.) ), Amazonian rainforest, Kaggle kernels, AID: Aerial Scene Classification (Xia et al., 2017) Visdrone-DET test-dev split comprises 1610 images. BioCAS 2015 will comprise an excellent combination of invited talks and tutorials from pioneers in the field as well as peer-reviewed special and regular sessions plus live demonstrations. Visdrone-DET testing split comprises 548 images. A multi-modal and mono-temporal data set for cloud removal. satellite-image-deepl-learning & ), pre-trained baseline model. Detection of settlements without electricity, 98 multi-temporal/multi-sensor tiles ( Sentinel-1, Sentinel-2, Landsat-8, VIIRS), per chip & per pixel labels (contains buildings, presence electricity). for year 2017 with cloud masks, Official Slovenian land use land cover layer as ground truth. The AISKYEYE team at Tianjin University Lab of Machine Learning and Data Mining has gathered the data for the VisDrone2019 benchmark dataset. Airbus Oil Storage Detection (Airbus, Mar 2021) 175 globally distributed aois. Since 2018 Microsoft research open data has been collaborating across the research community to collect datasets for a variety of categories. Paper: Chiu et al. 1980 image chips of 256 x 256 pixels in V1.0 spanning 66 tiles of Sentinel-2. The IEEE Biomedical Circuits and Systems Conference (BioCAS) serves as a premier international. Newest datasets at the top of each category (Instance segmentation, object detection, semantic segmentation, scene classification, other). Monthly building footprints and Planet imagery (4m. Paper: SEN12MS-CR - Ebel et al. 10 land cover categories from crops to vehicle small, 57 1x1km images, 3/16-band Worldview 3 imagery (0.3m-7.5m res. 34701 manually segmented 384x384 patches with cloud masks, Landsat 8 imagery (R,G,B,NIR; 30 m res. ), 6 cities, Paper: Mundhenk et al. : Search over 585 datasets for machine learning. Semi-supervised semantic segmentation, 19 cities and surroundings with multi-sensor tiles (VHR Aerial imagery 50cm res., Elevation model) & per pixel labels (contains landcover / landuse classes from UrbanAtlas 2012), Data. Classes: water, natural bare ground, artificial bare ground, woody vegetation, cultivated vegetation, (semi) natural vegetation, and permanent snow/ice. You signed in with another tab or window. Predict the chronological order of images taken at the same locations over 5 days, Kaggle kernels. ALCD Reference Cloud Masks (CNES, Oct 2018) 45 scene categories from airplane to wetland, 31,500 images (700 per category, 256x256 px), image chips taken from Google Earth (rich image variations in resolution, angle, geography all over the world), Download Link, Paper: Cheng et al. Aircraft bounding boxes, 103 images of worlwide airports (Pleiades, 0.5m res., 2560px). 2017, Inria Aerial Image Labeling (inria.fr)
over 2 years, 75 aois, landcover labels (7 categories), 2 competition tracks (Binary land cover classification & multi-class change detection). ), manual segmentations masks for Buildings, Woodland and Water, Paper: Boguszewski et al., 2020, 95-Cloud: A Cloud Segmentation Dataset (S. Mohajerani et. Road network labels, high-res Google Earth imagery, 21 regions, Paper: Liu et al. Manual labeling & active learning, Paper: Baetens et al. Load Visdrone-DET Dataset Training Subset in Python, Load Visdrone-DET Dataset Testing Subset in Python, Load Visdrone-DET Dataset Validation Subset in Python, Load Visdrone-DET Dataset Testing-DEV Subset in Python, How to use Visdrone-DET Dataset with PyTorch and TensorFlow in Python, Additional Information about Visdrone-DET Dataset. Dedicated to the free and open sharing of raw magnetic resonance imaging (MRI) datasets.. subset Landsat 8 scenes (30m res. ), SpaceNet Challenge Asset Library. Tree position, tree species and crown parameters, hyperspectral (1m res.) are present. On behalf of the Organizing Committee, I am happy to invite you to participate in the IEEE/CAS-EMB Biomedical Circuits and Systems Conference (BioCAS 2015), which will be held on October 22-24, 2015, at the historic Academy of Medicine in Atlanta, Georgia, USA. 2019, Statoil/C-CORE Iceberg Classifier Challenge (Statoil/C-CORE, Jan 2018) 2020. )., ca. IEEE Data Fusion Contest 2021 (IEEE, HP, SolarAid, Data Science Experts, Mar 2021) ), for a total of 11448 trajectories. Aerial imagery (0.13 m res.) Airbus Ship Detection Challenge (Airbus, Nov 2018) The challenge consists on predicting 3161 human trajectories, observing for each trajectory 8 consecutive ground-truth values (3.2 seconds) i.e., t7,t6,,t, in world plane coordinates (the so-called world plane Human-Human protocol) and forecasting the following 12 (4.8 seconds), i.e., t+1,,t+12. Paper: ), USDA Cropland Data Layer as ground truth. 155k 128x128px image chips with wind turbines (SPOT, 1.5m res.). : Human-verified labels on approximately 237K segments with 1000 classes are collected from the validation set of the YouTube-8M dataset. 685k building footprints, 3/8band Worldview-3 imagery (0.3m res. 2018, SpaceNet 3: Road Network Detection (CosmiQ Works, Radiant Solutions, Feb 2018) 124,422 Agricultural parcels, 2,433 Sentinel-2 image chip timeseries, France, panoptic labels (instance index + semantic label for each pixel). title={Detection and Tracking Meet Drones Challenge}. 2020. Paper: Xia et al. Building footprints (Rio de Janeiro), 3/8band Worldview-3 imagery (0.5m res. 2300 image chips, street geometries with location, shape and estimated travel time, 3/8band Worldview-3 imagery (0.3m res. ), Paper: Xu et al. 2343 image chips (drone imagery), 10 landcover categories (background, water, building flooded, building non-flooded, Paper: Wang et al., 2021, FloodNet Challenge (UMBC, Microsoft, Texas A&M, Dewberry, May 2021) Individual tree crown objects, height&area estimates, 100 million instances, 37 geographic sites across the US, DeepForest Python package, Paper: Weinstein et al. This repository has been archived by the owner. satellite imagery, LiDAR (0.80m pulse spacing, ASCII format), semantic labels, urban setting USA, baseline methods provided, Paper: Le Saux et al. 2015, UC Merced Land Use Dataset (UC Merced, Oct 2010) We do not host or distribute these datasets, vouch for their quality or fairness, or claim that you have a license to use the datasets. Check our our latest webinar to learn more! 48k building footprints (enhanced 3DBAG dataset, building height attributes), Capella Space SAR data (0.5m res., four polarizations) & Worldview-3 imagery (0.3m res. List of satellite image training datasets with annotations for computer vision and deep learning, The list is now archived. RarePlanes: Synthetic Data Takes Flight (CosmiQ Works, A.I.Reverie, June 2020) & Hayes D.J. 2019 Outcome Part A: Kunwar et al. : Explore datasets by size, category, modality (including X-ray, Ultrasound, Whole Slide Images, CT Scans, ECGs), and more. Intelinair, CVPR, Jan 2020) ), Paper: Mohajerani et al. Thank you for your contribution to the ML community! 12.6mil (Canada) & 125.2mil (USA) & 17.9mil (Uganda/Tanzania) & 11.3mil (Australia) building footprints, GeoJSON format, delineation based on Bing imagery using ResNet34 architecture. & RGB imagery (0.25m res. Agricultural Pattern Analysis, 21k aerial farmland images (RGB-NIR, USA, 2019 season, 512x512px chips), label masks for 6 field anomaly patterns (Cloud shadow, Double plant, Planter skip, Standing Water, Waterway and Weed cluster). Oil storage tank annotations, 98 worldwide images (SPOT, 1.2m res., 2560px). Visdrone-DET Dataset Citation Information. Also comes with binary classification tags for each subscene, describing what surface types, cloud types, etc. It should be noted that the dataset was gathered utilising a variety of drone platforms (i.e., drones of various types), in a variety of settings, and under a variety of weather and lighting circumstances. If you're a dataset owner and do not want your dataset to be included in this library, please get in touch through a. . The Street View House Numbers (SVHN) Dataset. IEEE Data Fusion Contest 2019 (IEEE, Mar 2019) List of aerial and satellite imagery datasets with annotations for computer vision and deep learning. ), Rotterdam, Netherlands. Bi-cubicly resampled to same number of pixels in each image to counter courser native resolution with higher off-nadir angles, Paper: Weir et al. In fact, TrajNet is a superset of diverse datasets that requires to train on four families of trajectories, namely 1) BIWI Hotel (orthogonal birds eye flight view, moving people), 2) Crowds UCY (3 datasets, tilted birds eye view, camera mounted on building or utility poles, moving people), 3) MOT PETS (multisensor, different human activities) and 4) Stanford Drone Dataset (8 scenes, high orthogonal birds eye flight view, different agents as people, cars etc. MiniFrance (Universit Bretagne-Sud and ONERA, Jul 2020) ), LiDAR point cloud and canopy height model, NOAA Fisheries Steller Sea Lion Population Count (NOAA, Jun 2017) Mark PhelpsTalk Title:The next wave of microelectronics integration: human biology & implantable devicesBio, Jan RabaeyTalk Title: "The Human Intranet"Bio, AliKhademhosseiniTalk Title:"Microengineered tissues for regenerative medicine and organs-on-a-chip applications"Bio.
The benchmarks section lists all benchmarks using a given dataset or any of 2019. Our favorite source for free datasets, collaboration, and competition is Kaggle. DroneDeploy Segmentation Dataset (DroneDeploy, Dec 2019) The engaging three-day single-track program, all of which is included in your registration, covers a wide range of topics, including but not limited to: On behalf of the Organizing Committee, I cordially invite you to participate in the 2015 Biomedical Circuits and Systems Conference and contribute to the continued success of this rapidly growing annual event at the intersection of medicine and engineering. Please see these fantastic ressources for more recent datasets:
), SpaceNet Challenge Asset Library, Paper: Van Etten et al. : A collection of aerial videos that can be used to train a variety of unmanned autonomous vehicles. 790k building footprints from Openstreetmap (2 label quality categories), aerial imagery (0.03-0.2m resolution, RGB, 11k 1024x1024 chips, COG format), 10 cities in Africa. Worldview-3 (8-band, 0.35cm res.) We use variants to distinguish between results evaluated on Building footprint masks, RGB aerial imagery (0.3m res. 32k car bounding boxes, aerial imagery (0.15m res. Sentinel-2 Cloud Mask Catalogue (Francis, A., et al., Nov 2020) Testing is requested on diverse partitions of BIWI Hotel, Crowds UCY, Stanford Drone Dataset, and is evaluated by a specific server (ground-truth testing data is unavailable for applicants). Multiple tracks: Semantic 3D reconstruction, Semantic Stereo, 3D-Point Cloud Classification. Corresponding imagery from drone, satellite and ground camera of 1,652 university buildings, Paper: Zheng et al. 8 classes (inc. cloud and cloud shadow) for 38 Sentinel-2 scenes (10 m res.). 2 categories ship and iceberg, 2-band HH/HV polarization SAR imagery, Kaggle kernels, Functional Map of the World Challenge (IARPA, Dec 2017) Drone imagery (0.1m res., RGB), labels (7 land cover catageories: building, clutter, vegetation, water, ground, car) & elevation data, baseline model implementation. Maritime object bounding boxes for 1k Sentinel-1 scenes (VH & VV polarizations), ancillary data (land/ice mask, bathymetry, wind speed, direction, quality). All bands resampled to 20m, stored as numpy arrays. 2 main categories corn and soybeans, Landsat 8 imagery (30m res. For example, ImageNet 3232 FloodNet (University of Maryland, Jun 2021) dash line, long line, zebra zone) & urban infrastructure (19 categories e.g. Local climate zone classification, 17 categories (10 urban e.g.
60 categories from helicopter to stadium, 1 million instances, Worldview-3 imagery (0.3m res.
boxes: tensor representing bounding box for the object of interest. and ImageNet 6464 are variants of the ImageNet dataset. Train a model on Visdrone-DET dataset with PyTorch in Python, dataloader = ds.pytorch(num_workers=0, batch_size=4, shuffle=False), Train a model on Visdrone-DET dataset with TensorFlow in Python, https://github.com/VisDrone/VisDrone-Dataset, Zhu, Pengfei and Wen, Longyin and Du, Dawei and Bian, Xiao and Fan, Heng and Hu, Qinghua and Ling, Haibin: Detection and Tracking Meet Drones Challenge, Zhu, Pengfei and Wen, Longyin and Du, Dawei and Bian, Xiao and Fan, Heng and Hu, Qinghua and Ling, Haibin, Visdrone-DET Dataset Licensing Information.
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