cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57760/sciencedb.33187
title: OpenSubstance: A High-Quality Measured Dataset of Multi-View and -Lighting Images and Shapes (Part 8)
title: OpenSubstance: A High-Quality Measured Dataset of Multi-View and -Lighting Images and Shapes (Part 8)

description: We present OpenSubstance, a high-quality measured dataset with 2.4 million high-dynamic-range images of 187 objects with a wide variety in shape and appearance, captured under 270 camera views and 1,637 lighting conditions, including 1,620 one-light-at-a-time, 8 environment, 8 linear, and 1 full-on illumination. For each image, the corresponding lighting condition, camera parameters, and foreground segmentation mask are provided. High-precision 3D geometry is also acquired for rigid objects. It takes 1 hour on average to capture one object with our custom-built high-performance lightstage and a top-grade commercial 3D scanner. We perform comprehensive quantitative evaluation on state-of-the-art techniques across different tasks, including single- and multi-view photometric stereo, as well as relighting. The project is publicly available at https://opensubstance.github.io/This dataset includes part of raw images data.
description: We present OpenSubstance, a high-quality measured dataset with 2.4 million high-dynamic-range images of 187 objects with a wide variety in shape and appearance, captured under 270 camera views and 1,637 lighting conditions, including 1,620 one-light-at-a-time, 8 environment, 8 linear, and 1 full-on illumination. For each image, the corresponding lighting condition, camera parameters, and foreground segmentation mask are provided. High-precision 3D geometry is also acquired for rigid objects. It takes 1 hour on average to capture one object with our custom-built high-performance lightstage and a top-grade commercial 3D scanner. We perform comprehensive quantitative evaluation on state-of-the-art techniques across different tasks, including single- and multi-view photometric stereo, as well as relighting. The project is publicly available at https://opensubstance.github.io/This dataset includes part of raw images data.
DOI: 10.57760/sciencedb.32802
title: OpenSubstance: A High-Quality Measured Dataset of Multi-View and -Lighting Images and Shapes (Part 7)
title: OpenSubstance: A High-Quality Measured Dataset of Multi-View and -Lighting Images and Shapes (Part 7)

description: We present OpenSubstance, a high-quality measured dataset with 2.4 million high-dynamic-range images of 187 objects with a wide variety in shape and appearance, captured under 270 camera views and 1,637 lighting conditions, including 1,620 one-light-at-a-time, 8 environment, 8 linear, and 1 full-on illumination. For each image, the corresponding lighting condition, camera parameters, and foreground segmentation mask are provided. High-precision 3D geometry is also acquired for rigid objects. It takes 1 hour on average to capture one object with our custom-built high-performance lightstage and a top-grade commercial 3D scanner. We perform comprehensive quantitative evaluation on state-of-the-art techniques across different tasks, including single- and multi-view photometric stereo, as well as relighting. The project is publicly available at https://opensubstance.github.io/This dataset includes part of raw images data.
description: We present OpenSubstance, a high-quality measured dataset with 2.4 million high-dynamic-range images of 187 objects with a wide variety in shape and appearance, captured under 270 camera views and 1,637 lighting conditions, including 1,620 one-light-at-a-time, 8 environment, 8 linear, and 1 full-on illumination. For each image, the corresponding lighting condition, camera parameters, and foreground segmentation mask are provided. High-precision 3D geometry is also acquired for rigid objects. It takes 1 hour on average to capture one object with our custom-built high-performance lightstage and a top-grade commercial 3D scanner. We perform comprehensive quantitative evaluation on state-of-the-art techniques across different tasks, including single- and multi-view photometric stereo, as well as relighting. The project is publicly available at https://opensubstance.github.io/This dataset includes part of raw images data.
DOI: 10.57760/sciencedb.32750
title: OpenSubstance: A High-Quality Measured Dataset of Multi-View and -Lighting Images and Shapes (Part 6)
title: OpenSubstance: A High-Quality Measured Dataset of Multi-View and -Lighting Images and Shapes (Part 6)

description: We present OpenSubstance, a high-quality measured dataset with 2.4 million high-dynamic-range images of 187 objects with a wide variety in shape and appearance, captured under 270 camera views and 1,637 lighting conditions, including 1,620 one-light-at-a-time, 8 environment, 8 linear, and 1 full-on illumination. For each image, the corresponding lighting condition, camera parameters, and foreground segmentation mask are provided. High-precision 3D geometry is also acquired for rigid objects. It takes 1 hour on average to capture one object with our custom-built high-performance lightstage and a top-grade commercial 3D scanner. We perform comprehensive quantitative evaluation on state-of-the-art techniques across different tasks, including single- and multi-view photometric stereo, as well as relighting. The project is publicly available at https://opensubstance.github.io/This dataset includes part of raw images data.
description: We present OpenSubstance, a high-quality measured dataset with 2.4 million high-dynamic-range images of 187 objects with a wide variety in shape and appearance, captured under 270 camera views and 1,637 lighting conditions, including 1,620 one-light-at-a-time, 8 environment, 8 linear, and 1 full-on illumination. For each image, the corresponding lighting condition, camera parameters, and foreground segmentation mask are provided. High-precision 3D geometry is also acquired for rigid objects. It takes 1 hour on average to capture one object with our custom-built high-performance lightstage and a top-grade commercial 3D scanner. We perform comprehensive quantitative evaluation on state-of-the-art techniques across different tasks, including single- and multi-view photometric stereo, as well as relighting. The project is publicly available at https://opensubstance.github.io/This dataset includes part of raw images data.
DOI: 10.57760/sciencedb.32337
title: OpenSubstance: A High-Quality Measured Dataset of Multi-View and -Lighting Images and Shapes (Part 5)
title: OpenSubstance: A High-Quality Measured Dataset of Multi-View and -Lighting Images and Shapes (Part 5)

description: We present OpenSubstance, a high-quality measured dataset with 2.4 million high-dynamic-range images of 187 objects with a wide variety in shape and appearance, captured under 270 camera views and 1,637 lighting conditions, including 1,620 one-light-at-a-time, 8 environment, 8 linear, and 1 full-on illumination. For each image, the corresponding lighting condition, camera parameters, and foreground segmentation mask are provided. High-precision 3D geometry is also acquired for rigid objects. It takes 1 hour on average to capture one object with our custom-built high-performance lightstage and a top-grade commercial 3D scanner. We perform comprehensive quantitative evaluation on state-of-the-art techniques across different tasks, including single- and multi-view photometric stereo, as well as relighting. The project is publicly available at https://opensubstance.github.io/This dataset includes part of raw images data.
description: We present OpenSubstance, a high-quality measured dataset with 2.4 million high-dynamic-range images of 187 objects with a wide variety in shape and appearance, captured under 270 camera views and 1,637 lighting conditions, including 1,620 one-light-at-a-time, 8 environment, 8 linear, and 1 full-on illumination. For each image, the corresponding lighting condition, camera parameters, and foreground segmentation mask are provided. High-precision 3D geometry is also acquired for rigid objects. It takes 1 hour on average to capture one object with our custom-built high-performance lightstage and a top-grade commercial 3D scanner. We perform comprehensive quantitative evaluation on state-of-the-art techniques across different tasks, including single- and multi-view photometric stereo, as well as relighting. The project is publicly available at https://opensubstance.github.io/This dataset includes part of raw images data.
DOI: 10.57760/sciencedb.32194
title: OpenSubstance: A High-Quality Measured Dataset of Multi-View and -Lighting Images and Shapes (Part 4)
title: OpenSubstance: A High-Quality Measured Dataset of Multi-View and -Lighting Images and Shapes (Part 4)

description: We present OpenSubstance, a high-quality measured dataset with 2.4 million high-dynamic-range images of 187 objects with a wide variety in shape and appearance, captured under 270 camera views and 1,637 lighting conditions, including 1,620 one-light-at-a-time, 8 environment, 8 linear, and 1 full-on illumination. For each image, the corresponding lighting condition, camera parameters, and foreground segmentation mask are provided. High-precision 3D geometry is also acquired for rigid objects. It takes 1 hour on average to capture one object with our custom-built high-performance lightstage and a top-grade commercial 3D scanner. We perform comprehensive quantitative evaluation on state-of-the-art techniques across different tasks, including single- and multi-view photometric stereo, as well as relighting. The project is publicly available at https://opensubstance.github.io/This dataset includes part of raw images data.
description: We present OpenSubstance, a high-quality measured dataset with 2.4 million high-dynamic-range images of 187 objects with a wide variety in shape and appearance, captured under 270 camera views and 1,637 lighting conditions, including 1,620 one-light-at-a-time, 8 environment, 8 linear, and 1 full-on illumination. For each image, the corresponding lighting condition, camera parameters, and foreground segmentation mask are provided. High-precision 3D geometry is also acquired for rigid objects. It takes 1 hour on average to capture one object with our custom-built high-performance lightstage and a top-grade commercial 3D scanner. We perform comprehensive quantitative evaluation on state-of-the-art techniques across different tasks, including single- and multi-view photometric stereo, as well as relighting. The project is publicly available at https://opensubstance.github.io/This dataset includes part of raw images data.
DOI: 10.57760/sciencedb.31652
title: OpenSubstance: A High-Quality Measured Dataset of Multi-View and -Lighting Images and Shapes (Part 3)
title: OpenSubstance: A High-Quality Measured Dataset of Multi-View and -Lighting Images and Shapes (Part 3)

description: We present OpenSubstance, a high-quality measured dataset with 2.4 million high-dynamic-range images of 187 objects with a wide variety in shape and appearance, captured under 270 camera views and 1,637 lighting conditions, including 1,620 one-light-at-a-time, 8 environment, 8 linear, and 1 full-on illumination. For each image, the corresponding lighting condition, camera parameters, and foreground segmentation mask are provided. High-precision 3D geometry is also acquired for rigid objects. It takes 1 hour on average to capture one object with our custom-built high-performance lightstage and a top-grade commercial 3D scanner. We perform comprehensive quantitative evaluation on state-of-the-art techniques across different tasks, including single- and multi-view photometric stereo, as well as relighting. The project is publicly available at https://opensubstance.github.io/This dataset includes part of raw images data.
description: We present OpenSubstance, a high-quality measured dataset with 2.4 million high-dynamic-range images of 187 objects with a wide variety in shape and appearance, captured under 270 camera views and 1,637 lighting conditions, including 1,620 one-light-at-a-time, 8 environment, 8 linear, and 1 full-on illumination. For each image, the corresponding lighting condition, camera parameters, and foreground segmentation mask are provided. High-precision 3D geometry is also acquired for rigid objects. It takes 1 hour on average to capture one object with our custom-built high-performance lightstage and a top-grade commercial 3D scanner. We perform comprehensive quantitative evaluation on state-of-the-art techniques across different tasks, including single- and multi-view photometric stereo, as well as relighting. The project is publicly available at https://opensubstance.github.io/This dataset includes part of raw images data.
DOI: 10.15468/dl.5fhqqp
title: Occurrence Download

description: A dataset containing 17679 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is China",
 "GadmGid is CHN.20_1",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 17679 records from 107 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059974-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57760/sciencedb.31647
title: OpenSubstance: A High-Quality Measured Dataset of Multi-View and -Lighting Images and Shapes (Part 2)
title: OpenSubstance: A High-Quality Measured Dataset of Multi-View and -Lighting Images and Shapes (Part 2)

description: We present OpenSubstance, a high-quality measured dataset with 2.4 million high-dynamic-range images of 187 objects with a wide variety in shape and appearance, captured under 270 camera views and 1,637 lighting conditions, including 1,620 one-light-at-a-time, 8 environment, 8 linear, and 1 full-on illumination. For each image, the corresponding lighting condition, camera parameters, and foreground segmentation mask are provided. High-precision 3D geometry is also acquired for rigid objects. It takes 1 hour on average to capture one object with our custom-built high-performance lightstage and a top-grade commercial 3D scanner. We perform comprehensive quantitative evaluation on state-of-the-art techniques across different tasks, including single- and multi-view photometric stereo, as well as relighting. The project is publicly available at https://opensubstance.github.io/This dataset includes part of raw images data.
description: We present OpenSubstance, a high-quality measured dataset with 2.4 million high-dynamic-range images of 187 objects with a wide variety in shape and appearance, captured under 270 camera views and 1,637 lighting conditions, including 1,620 one-light-at-a-time, 8 environment, 8 linear, and 1 full-on illumination. For each image, the corresponding lighting condition, camera parameters, and foreground segmentation mask are provided. High-precision 3D geometry is also acquired for rigid objects. It takes 1 hour on average to capture one object with our custom-built high-performance lightstage and a top-grade commercial 3D scanner. We perform comprehensive quantitative evaluation on state-of-the-art techniques across different tasks, including single- and multi-view photometric stereo, as well as relighting. The project is publicly available at https://opensubstance.github.io/This dataset includes part of raw images data.
DOI: 10.57760/sciencedb.31147
title: OpenSubstance: A High-Quality Measured Dataset of Multi-View and -Lighting Images and Shapes (Part 1)
title: OpenSubstance: A High-Quality Measured Dataset of Multi-View and -Lighting Images and Shapes (Part 1)

description: We present OpenSubstance, a high-quality measured dataset with 2.4 million high-dynamic-range images of 187 objects with a wide variety in shape and appearance, captured under 270 camera views and 1,637 lighting conditions, including 1,620 one-light-at-a-time, 8 environment, 8 linear, and 1 full-on illumination. For each image, the corresponding lighting condition, camera parameters, and foreground segmentation mask are provided. High-precision 3D geometry is also acquired for rigid objects. It takes 1 hour on average to capture one object with our custom-built high-performance lightstage and a top-grade commercial 3D scanner. We perform comprehensive quantitative evaluation on state-of-the-art techniques across different tasks, including single- and multi-view photometric stereo, as well as relighting. The project is publicly available at https://opensubstance.github.io/This dataset includes part of raw images data.
description: We present OpenSubstance, a high-quality measured dataset with 2.4 million high-dynamic-range images of 187 objects with a wide variety in shape and appearance, captured under 270 camera views and 1,637 lighting conditions, including 1,620 one-light-at-a-time, 8 environment, 8 linear, and 1 full-on illumination. For each image, the corresponding lighting condition, camera parameters, and foreground segmentation mask are provided. High-precision 3D geometry is also acquired for rigid objects. It takes 1 hour on average to capture one object with our custom-built high-performance lightstage and a top-grade commercial 3D scanner. We perform comprehensive quantitative evaluation on state-of-the-art techniques across different tasks, including single- and multi-view photometric stereo, as well as relighting. The project is publicly available at https://opensubstance.github.io/This dataset includes part of raw images data.
DOI: 10.57760/sciencedb.33923
title: figures and tables for the article "Intranasal booster drives class switching and homing of memory B cells for mucosal IgA response"
title: figures and tables for the article "Intranasal booster drives class switching and homing of memory B cells for mucosal IgA response"

description: This zip package includes all the figures and tables involving in the article "Intranasal booster drives class switching and homing of memory B cells for mucosal IgA response" submitted to JCI Insight
description: This zip package includes all the figures and tables involving in the article "Intranasal booster drives class switching and homing of memory B cells for mucosal IgA response" submitted to JCI Insight
DOI: 10.15468/dl.n83bcd
title: Occurrence Download

description: A dataset containing 223056 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry MULTIPOLYGON(((108.26449 30.39733,108.00197 29.23897,107.3575 29.08274,107.90402 27.9875,107.76148 27.39211,108.93975 27.50386,108.7931 27.04112,109.47979 27.05249,110.35964 28.88738,111.47401 29.28061,111.09203 30.1591,111.31702 30.47557,110.34079 30.78238,110.3372 31.4018,110.04181 30.80481,108.26449 30.39733)))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 223056 records from 366 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059962-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qvqu3k
title: Occurrence Download

description: A dataset containing 1964 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Dysithamnus xanthopterus Burmeister, 1856"
 ]
}

 The dataset includes 1964 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003227-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mhjiw9
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Archaea",
 "DecimalLatitude is greater than 37.3281617701048",
 "DecimalLatitude is less than 38.8048024796949",
 "DecimalLongitude is greater than -111.76703703656",
 "DecimalLongitude is less than -110.522443367931"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004604-180824113759888/datasets/export for details.
DOI: 10.15468/dl.bmwyxd
title: Occurrence Download

description: A dataset containing 628 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Nisaetus bartelsi (Stresemann, 1924)"
 ]
}

 The dataset includes 628 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058238-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h45vjk
title: Occurrence Download

description: A dataset containing 529920 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Country is one of (Canada, Mexico, United States of America)",
 "EventDate is greater than or equal to 2024-02-16",
 "EventDate is less than or equal to 2024-03-17",
 {
 "not" : {
 "Issue" : [
 "is one of (Basis of record invalid, Coordinate reprojection failed, Coordinate reprojection suspicious, Coordinate precision invalid, Coordinate uncertainty meters invalid, Country mismatch, Country invalid, Geodetic datum invalid, Presumed swapped coordinate, Presumed negated longitude, Presumed negated latitude, Country coordinate mismatch)"
 ]
 }
 }
 ]
}

 The dataset includes 529920 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0151835-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xspcgl
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Archaea",
 "DecimalLatitude is greater than 31.4955619906106",
 "DecimalLatitude is less than 32.0394246308873",
 "DecimalLongitude is greater than -106.773915029922",
 "DecimalLongitude is less than -106.134514572739"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004617-180824113759888/datasets/export for details.
DOI: 10.15468/dl.ezvlqr
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Archaea",
 "DecimalLatitude is greater than 33.4740331124373",
 "DecimalLatitude is less than 34.1146914632436",
 "DecimalLongitude is greater than -81.1914881116838",
 "DecimalLongitude is less than -80.2784161781147"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004636-180824113759888/datasets/export for details.
DOI: 10.15468/dl.f7jhas
title: Occurrence Download

description: A dataset containing 235 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-102.08940 15.39198,-91.46562 15.39198,-91.46562 19.64369,-102.08940 19.64369,-102.08940 15.39198))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Leopardus wiedii (Schinz, 1821)"
 ]
}

 The dataset includes 235 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0289352-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.