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.


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 Guillaumin (Amazon.com)
  • Thomas Dideriksen (Amazon.com)
  • Kenan Deng (Amazon.com)
  • Himanshu Arora (Amazon.com)
  • Arnab Dhua (Amazon.com)
  • Jasmine Collins (UC Berkeley)
  • Shubham Goel (UC Berkeley)
  • Jitendra Malik (UC Berkeley)
Note: If you use this dataset for academic publication, we ask to attribute credit by citing our soon-to-appear arxiv.org paper describing data collection, curation and benchmarks.

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.