Visual Bank Launches Qlean Dataset for AI Development with Abstract Image Backgrounds

Visual Bank Introduces Qlean Dataset: A Step Forward in AI Development

Visual Bank Inc., located in Minato-ku, Tokyo and led by CEO Masanori Nagai, is making significant advances in providing AI training data solutions through its subsidiary Amana Images. The company has recently added a new resource to its well-known Qlean Dataset, now featuring an array of abstract motif background images. This addition serves to enhance their exclusive set of AI development resources branded as AI Data Recipes.

Understanding the New Abstract Motif Background Image Dataset

This latest offering, the "Abstract Motif Background Image Dataset," includes visual materials that encompass themes such as water, flowers, light, and abstract gradients. Each image is in JPEG format and consists of 400 high-resolution files, each with a minimum long edge exceeding 2,400 pixels. For those interested in exploring the dataset further, a detailed sample can be found here.

Use Cases of the Abstract Motif Background Image Dataset

1. Training Generative AI and Image Synthesis Models
The dataset is ideally suited for training background generation AIs and image synthesis models, as it includes nature-inspired abstract motifs. The vivid colors and smooth compositions are particularly beneficial for enhancing the quality of diffusion models and generative AIs.

2. Development of Automated Design Generation and Graphic AIs
Covering universal abstract visual materials often used in advertisements or UI backgrounds, this dataset is a valuable resource for developing automated design generation AIs and graphic layout support tools. Its applications extend to improving efficiency in creative processes and facilitating automated banner creation.

3. Researching Visual Feature Extraction and Image Classification AIs
The diverse texture, color, and shape components make this dataset perfect for use in visual feature extraction models and color classification AI research. Notably, it plays a critical role in boosting accuracy in recognizing abstract compositions and non-representational elements within the field of computer vision.

4. Application in Video Synthesis and Media Production
With high-resolution materials above 2,400 pixels, this dataset is suitable for video backgrounds, motion graphics, and projection visuals. It aids the development of AI-assisted tools within video production and media art domains.

5. Utilization in Design Education and AI Ethics Research
Handling abstract motifs enables the dataset to be used as learning data for AI that avoids copyright risks. It is beneficial for generative AI training programs in educational institutions and for research into ethical considerations in the creative AI field.

Unique Characteristics of Qlean Dataset

- Research and Commercial Use Compatibility

Qlean Dataset ensures that all data obtained and utilized for AI development comes with consent from the subjects portrayed, adhering to privacy policies in various countries. This guarantees safe usage for both research and commercial ventures.

- Quick and ROI Maximization through AI Data Recipes

The unique format of providing data sets via AI Data Recipes allows businesses to procure data with reduced initial investments, maximizing return on investment.

- Tailored Data Sets on Demand

For unique data that is not included in the AI Data Recipes, the Qlean Dataset capabilities allow for the customization and provision of specifically tailored datasets according to individual requirements.

Academia Support Program by Qlean Dataset

In a bid to support academic institutions, Visual Bank is rolling out a complimentary program for the provision of datasets from the Qlean Dataset to universities, research institutes, and nonprofit tech development teams. They offer over 500,000 pieces of data across more than 80 categories, including images, audio, video, and text. This aims to resolve the challenge faced by researchers in accessing high-quality, rights-cleared datasets. For more information, visit here.

Visual Bank is focused on building and providing next-generation data infrastructure with the mission to unleash the potential of all data, particularly delivering solutions such as THE PEN for manga artists and the Qlean Dataset through its subsidiary Amana Images. Furthermore, Visual Bank has been selected for the national research and development program "GENIAC," accelerating its initiatives towards social implementation.

CEO: Masanori Nagai
Location: 6F C-Cube Minami Aoyama Building, 7-1-7 Minami Aoyama, Minato-ku, Tokyo
Visual Bank Corporate URL: https://visual-bank.co.jp/
Amana Images Corporate URL: https://amanaimages.com/about/