Amazon Berkeley Objects (ABO) Dataset

A CC BY-NC 4.0-licensed dataset of Amazon products with metadata, catalog images, and 3D models.

Catalog Images

Main product image

For the 147,702 products, we provide 398,212 unique catalog images in high resolution.

360º Images

360-view images

For more than 8,200 products, the dataset includes a sequence of 72 images, capturing the product every 5º in azimuth, for a total of 586,584 images.

3D Models

The dataset contains high-quality 3D models with 4K texture maps for physically based rendering for more than 7'900 products. The models are provided in the standard glTF 2.0 format.

Renderings

Rendered product image

For products with 3D models, we provide rendered images for 91 viewpoints on the upper icosphere, with varying azimuth and elevation.

Environments

Rendered product image

For each model and viewpoint, 3 different environment maps are used to provide renderings with varied lighting, for a total of 2.1 million images.

Geometry

Surface normals

For each rendering, we provide the camera parameters, the object segmentation mask as well as dense normals and depth maps.

Materials

Segmentation mask

As well as texture maps of SVBRDF properties: base color, metallic and roughness.


Explore

Explore the 147,702 products in ABO by specifying keywords of product names, product type and choosing to show only products with 360º view images and/or 3D models.

Instructions
  1. Activate the exploration tool by loading the metadata (68 Mb)
  2. Use the filter form to narrow down on products of interest
  3. Click on product thumbnails to toggle the visualisation of product metadata (partial), images, 360º images and 3D models when available.
Filters
Loading data: 0%
Preview of dataset exploration

Download

This work is licensed under the Creative Commons Attribution-NonCommercial 4.0 International Public License (CC BY-NC 4.0). To obtain a copy of this license, see LICENSE-CC-BY-NC-4.0.txt in the archive, visit CreativeCommons.org or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.

Under the following terms:

Creative Commons License


The following archives are available for download:


Attribution

Credit for the data, including all images and 3D models, must be given to:

Amazon.com

Credit for building the dataset, archives and benchmark sets must be given to:

  • Matthieu GuillauminAmazon.com
  • Thomas DideriksenAmazon.com
  • Kenan DengAmazon.com
  • Himanshu AroraAmazon.com
  • Arnab DhuaAmazon.com
  • Xi (Brian) ZhangAmazon.com
  • Tomas Yago-VicenteAmazon.com
  • Jasmine CollinsUC Berkeley
  • Shubham GoelUC Berkeley
  • Jitendra MalikUC Berkeley

If you use this dataset for publication, we kindly ask you to attribute credit by citing our CVPR 2022 paper, or the version on arxiv.org, providing detailed description of the dataset and benchmarks:

@article{collins2022abo,
  title={ABO: Dataset and Benchmarks for Real-World 3D Object Understanding},
  author={Collins, Jasmine and Goel, Shubham and Deng, Kenan and Luthra, Achleshwar and
          Xu, Leon and Gundogdu, Erhan and Zhang, Xi and Yago Vicente, Tomas F and
          Dideriksen, Thomas and Arora, Himanshu and Guillaumin, Matthieu and
          Malik, Jitendra},
  journal={CVPR},
  year={2022}
}

Publications and links

Below is the list of publications known to use ABO:

Externally contributed data and code for ABO can be found at those locations:


Cloud Usage (AWS)

The ABO dataset is directly available on Amazon S3 at s3://amazon-berkeley-objects/, with the same structure as in the archives (see README).

In particular, the metadata is loadable in Amazon Athena, using the following SQL table creation statements:

CREATE EXTERNAL TABLE IF NOT EXISTS `default`.`abo_listings` (
  `brand` array < struct < language_tag:string, value:string >  >,
  `bullet_point` array < struct < language_tag:string, value:string >  >,
  `color` array < struct < language_tag:string, value:string >  >,
  `color_code` array < string >,
  `country` string,
  `domain_name` string,
  `fabric_type` array < struct < language_tag:string, value:string >  >,
  `finish_type` array < struct < language_tag:string, value:string >  >,
  `item_dimensions` struct < height:struct < normalized_value:struct < unit:string, value:float >,  value:float, unit:string >,  length:struct < normalized_value:struct < unit:string, value:float >,  value:float, unit:string >,  width:struct < normalized_value:struct < unit:string, value:float >,  value:float, unit:string >  >,
  `item_id` string,
  `item_keywords` array < struct < language_tag:string, value:string >  >,
  `item_name` array < struct < language_tag:string, value:string >  >,
  `item_shape` array < struct < language_tag:string, value:string >  >,
  `item_weight` array < struct < normalized_value:struct < unit:string, value:float >,  value:float, unit:string >  >,
  `main_image_id` string,
  `marketplace` string,
  `material` array < struct < language_tag:string, value:string >  >,
  `model_name` array < struct < language_tag:string, value:string >  >,
  `model_number` array < struct < language_tag:string, value:string >  >,
  `model_year` array < struct < language_tag:string, value:string >  >,
  `node` array < struct < node_id:bigint, path:string >  >,
  `other_image_id` array < string >,
  `pattern` array < struct < language_tag:string, value:string >  >,
  `product_description` array < struct < language_tag:string, value:string >  >,
  `product_type` array < struct < value:string >  >,
  `spin_id` string,
  `style` array < struct < language_tag:string, value:string >  >,
  `3dmodel_id` string
)
ROW FORMAT SERDE
  'org.openx.data.jsonserde.JsonSerDe'
WITH SERDEPROPERTIES (
  'serialization.format' = '1'
)
LOCATION
  's3://amazon-berkeley-objects/listings/metadata/'
TBLPROPERTIES (
  'has_encrypted_data'='false'
)

CREATE EXTERNAL TABLE IF NOT EXISTS `default`.`abo_images`(
  `image_id` string,
  `height` bigint,
  `width` bigint,
  `path` string
)
ROW FORMAT SERDE
  'org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe'
WITH SERDEPROPERTIES (
  'serialization.format' = ',',
  'field.delim' = ',',
  'skip.header.line.count'='1'
)
LOCATION
  's3://amazon-berkeley-objects/images/metadata/'
TBLPROPERTIES (
  'has_encrypted_data'='false'
)

CREATE EXTERNAL TABLE IF NOT EXISTS `default`.`abo_spins`(
  `spin_id` string,
  `azimuth` bigint,
  `image_id` string,
  `height` bigint,
  `width` bigint,
  `path` string
)
ROW FORMAT SERDE
  'org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe'
WITH SERDEPROPERTIES (
  'serialization.format' = ',',
  'field.delim' = ',',
  'skip.header.line.count'='1'
)
LOCATION
  's3://amazon-berkeley-objects/spins/metadata/'
TBLPROPERTIES (
  'has_encrypted_data'='false'
)

CREATE EXTERNAL TABLE IF NOT EXISTS `default`.`abo_3dmodels`(
  `3dmodel_id` string,
  `path` string,
  `meshes` bigint,
  `materials` bigint,
  `textures` bigint,
  `images` bigint,
  `image_height_max` bigint,
  `image_height_min` bigint,
  `image_width_max` bigint,
  `image_width_min` bigint,
  `vertices` bigint,
  `faces` bigint,
  `extent_x` float,
  `extent_y` float,
  `extent_z` float
  )
ROW FORMAT SERDE
  'org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe'
WITH SERDEPROPERTIES (
  'serialization.format' = ',',
  'field.delim' = ',',
  'skip.header.line.count'='1'
)
LOCATION
  's3://amazon-berkeley-objects/3dmodels/metadata/'
TBLPROPERTIES (
  'has_encrypted_data'='false'
)

Acknowledgements and Credits

This webpage is built with:

including GLTFLoader, RGBELoader and OrbitControls.
*
glb-viewer was modified to add support for OrbitControls, lighting from environment map and deferred rendering.