Auto-generated structured data of Adobe Analytics (v2.0) from table Fields

Cost per week on document-related tasks for each industry (USD).

Adobe Inc. operates as a diversified software company worldwide. It operates through three segments: Digital Media, Digital Experience, and Publishing and Advertising. The Digital Media segment offers products, services, and solutions that enable individuals, teams, and enterprises to create, publish, and promote content; and Document Cloud, a unified cloud-based document services platform. Its flagship product is Creative Cloud, a subscription service that allows members to access its creative products. This segment serves content creators, workers, marketers, educators, enthusiasts, communicators, and consumers. The Digital Experience segment provides an integrated platform and set of applications and services that enable brands and businesses to create, manage, execute, measure, monetize, and optimize customer experiences from analytics to commerce. This segment serves marketers, advertisers, agencies, publishers, merchandisers, merchants, web analysts, data scientists, developers, and executives across the C-suite. The Publishing and Advertising segment offers products and services, such as e-learning solutions, technical document publishing, web conferencing, document and forms platform, web application development, and high-end printing, as well as Advertising Cloud offerings. The company offers its products and services directly to enterprise customers through its sales force and local field offices, as well as to end users through app stores and through its website at adobe.com. It also distributes products and services through a network of distributors, value-added resellers, systems integrators, software vendors and developers, retailers, and original equipment manufacturers. The company was formerly known as Adobe Systems Incorporated and changed its name to Adobe Inc. in October 2018. Adobe Inc. was founded in 1982 and is headquartered in San Jose, California.

A complete list of live websites using the Adobe Creative Cloud technology, compiled through global website indexing conducted by WebTechSurvey.

A complete list of live websites using the Adobe Analytics technology, compiled through global website indexing conducted by WebTechSurvey.

AdobeVFR dataset covers 2,383 classes of popular fonts in graphics design. It is made up of the following four parts:

1. Synthetic Data

1.1 VFR_syn_train 1.2 VFR_syn_val

To create a sufficiently large set of synthetic training data, we render long English words sampled from a large corpus, and generate tightly cropped, gray-scale, and size-normalized text images. For each of the 2383 classes, we assign 1,000 images for training, and 100 for validation, which are denoted as VFR_syn_train and VFR_syn_val, respectively.

1. Real-world Data

2.1 VFR_real_test 2.2 VFR_real_u

We collected 201,780 text images from various typography forums, where people post these images seeking help from experts to identify the fonts. Most of them come with hand-annotated font labels which may be inaccurate. Unfortunately, only a very small portion of them fall into our list of 2,383 fonts. All images are first converted into gray scale. Those images with our target class labels are then selected and inspected by independent experts if their labels are correct. Images with verified labels are then manually cropped with tight bounding boxes and normalized proportionally in size, to be with the identical height of 105 pixels. Finally, we obtain 4,384 real-world test images with reliable labels, covering 617 classes (out of 2,383), as the VFR_real_test set. Compared to the synthetic data, these images typically have much larger appearance variations caused by scaling, background clutter, lighting, noise, perspective distortions, and compression artifacts.

Removing the 4,384 labeled images from the full set, we are left with 197,396 unlabeled real-world images which we denote as VFR_real_u. In our paper, those unlabeled data were utilized to pre-train a ``shared-feature'' extraction subnetwork to reduce the domain gap.

[1.0] In current release, we ONLY INCLUDE VFR_real_test and VFR_real_u, due to certain IP concerns on generating and releasing the synthetic data from copyrighted fonts.

We instead include a fontlist that speicifies the 2,383 font classes that we used. With an Adobe Creative Cloud subscription, one could download those font files (.otf) and render (unlimited) synthetic images.

We are still working hard to get our original VFR_syn_train and VFR_syn_val sucessfully released. Before then, if you're interested in following our expeirments, please don't hesistate to send an email to: masterwant@gmail.com and I'll try my best to help.

[1.1] Synthetic data added for training and validation, in bcf format. To see how to process bcf data, sample codes are provided to be used with cuda-convenet. Note those are only my own experiment codes and are not in any way optimized for product-level usage.

This dataset ('Licensed Material') is made available to the scientific community for non-commercial research purposes such as academic research, teaching, scientific publications or personal experimentation. Permission is granted by Zhangyang Wang (the 'Owner') to you (the 'Licensee') to use, copy and distribute the Licensed Material in accordance with the following terms and conditions:

Licensee must include a reference to the following publication in any published work that makes use of the Licensed Material:

​​Z. Wang, J. Yang, H. Jin, E. Shechtman, A. Agarwala, J. Brandt and T. Huang, “DeepFont: Identify Your Font from An Image”, In Proceedings of ACM International Conference on Multimedia (ACM MM) , 2015.

If Licensee alters the content of the Licensed Material or creates any derivative work, Licensee must include in the altered Licensed Material or derivative work prominent notices to ensure that any recipients know that they are not receiving the original Licensed Material.

Licensee may not use or distribute the Licensed Material or any derivative work for commercial purposes including but not limited to, licensing or selling the Licensed Material or using the Licensed Material for commercial gain.

The Licensed Material is provided 'AS IS', without any express or implied warranties. Owner does not accept any responsibility for errors or omissions in the Licensed Material.

This original license notice must be retained in all copies or derivatives of the Licensed Material.

All rights not expressly granted to the Licensee are reserved by Owner.

https://www.dropbox.com/sh/o320sowg790cxpe/AADDmdwQ08GbciWnaC20oAmna?dl=0

A complete list of live websites using the Adobe Audience Manager technology, compiled through global website indexing conducted by WebTechSurvey.

Overall averages for time and cost spent on document-related tasks at work.

kyeda/adobe-dataset dataset hosted on Hugging Face and contributed by the HF Datasets community

The total revenue of Adobe's digital media segment has grown steadily since 2016. In 2024, Adobe's digital media segment, which includes the creative cloud (CC) and document cloud businesses, had a revenue of approximately ***** billion U.S. dollars. The figure is expected to grow substantially by 2025, with the possibility of reaching over ** billion U.S. dollars.

A complete list of live websites using the Adobe Target technology, compiled through global website indexing conducted by WebTechSurvey.

This statistic shows the number of active subscriptions to Adobe's Creative Cloud service from 2013 to 2016, with forecasts for 2017 and 2024. As of 2017, Adobe was thought to have approximately ** million creative cloud subscribers.

Here are a few use cases for this project:

1. Document Management Systems: The "Adobe-Annotation-Phase-1-Filtered Dataset" can serve as an aid in developing advanced document management systems where different components of a document are algorithmically recognized. Having this ability could simplify searching, indexing, and managing vast amounts of documents, improving efficiency and productivity in the business.

2. Digital Archiving: Libraries, universities, and museums could use the model to transform physical documents into structured digital ones, while preserving their components for easier searching and interpretation.

3. Accessibility Solutions: This dataset can be utilized to convert printed text into various accessible formats for visually impaired individuals. For instance, after detecting the components in the printed publications, an algorithm can then convert them into speech or Braille formats.

4. Educational Technology: This model could be applied in EdTech products to help students to better understand the structure of different text-types. For instance, when learning about academic paper structures, the model could identify and highlight components such as headings, footnotes, etc.

5. Legal Document Processing: Law firms could use the model to automate the process of navigating through complex legal documents. The model could identify and categorize various components making it easier to analyze, understand, and reference particular sections.

Percentage of companies in each industry utilizing AI for document tasks, as shown in the infographic.

This dataset provides information about the number of properties, residents, and average property values for Adobe Street cross streets in Concord, CA.

Adobe Systems reported $5.06 in EPS Earnings Per Share for its fiscal quarter ending in May of 2025. Data for Adobe Systems | ADBE - EPS Earnings Per Share including historical, tables and charts were last updated by Trading Economics this last September in 2025.

In fiscal year 2024, Adobe's revenue by geographical region are as follows: Americas: $12.89 B, Asia: $3.06 B, EMEA: $5.55 B.

This dataset provides information about the number of properties, residents, and average property values for Adobe Drive cross streets in Pittsburgh, PA.

Adobe Inc. operates as a diversified software company worldwide. It operates through three segments: Digital Media, Digital Experience, and Publishing and Advertising. The Digital Media segment offers products, services, and solutions that enable individuals, teams, and enterprises to create, publish, and promote content; and Document Cloud, a unified cloud-based document services platform. Its flagship product is Creative Cloud, a subscription service that allows members to access its creative products. This segment serves content creators, workers, marketers, educators, enthusiasts, communicators, and consumers. The Digital Experience segment provides an integrated platform and set of applications and services that enable brands and businesses to create, manage, execute, measure, monetize, and optimize customer experiences from analytics to commerce. This segment serves marketers, advertisers, agencies, publishers, merchandisers, merchants, web analysts, data scientists, developers, and executives across the C-suite. The Publishing and Advertising segment offers products and services, such as e-learning solutions, technical document publishing, web conferencing, document and forms platform, web application development, and high-end printing, as well as Advertising Cloud offerings. The company offers its products and services directly to enterprise customers through its sales force and local field offices, as well as to end users through app stores and through its website at adobe.com. It also distributes products and services through a network of distributors, value-added resellers, systems integrators, software vendors and developers, retailers, and original equipment manufacturers. The company was formerly known as Adobe Systems Incorporated and changed its name to Adobe Inc. in October 2018. Adobe Inc. was founded in 1982 and is headquartered in San Jose, California.

Adobe Systems stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.