Few-Shot Dog Images for Generative Adversarial Network Training

A collection of images of dogs intended for few-shot image synthesis research, as referenced in the 2021 arXiv paper 'Towards Faster and Stabilized GAN Training for High-fidelity Few-shot Image Synthesis'. It is hosted by the 'huggan' organization and was last updated in April 2022. The specific row count, column structure, and file size are not provided in the input.

Use Cases

• Fine-tune a Generative Adversarial Network (GAN) for few-shot image synthesis using the provided dog images.
• Benchmark image generation models on a few-shot learning task with the dog image modality.
• Study the stabilization of GAN training protocols as outlined in the associated arXiv paper using this image collection.

Strengths

• Dataset is associated with a peer-reviewed arXiv research paper from 2021, providing academic context.
• The dataset is tagged with the modality 'image', confirming its content type.
• It is categorized under the size 'n1 K', indicating it contains over 1,000 data points.

Limitations

• The dataset description is incomplete, lacking concrete details on the number of images, resolution, or specific breeds.
• No sample data, column definitions, or file formats are provided, making initial assessment difficult.
• The dataset's last known update was in 2022, which may limit its relevance for benchmarking against the latest models.

Provenance

Source

huggan organization on Hugging Face, associated with the arXiv paper 'Towards Faster and Stabilized GAN Training for High-fidelity Few-shot Image Synthesis'.

Collection Method

Presumably collected or generated for research on few-shot GAN training, as per the linked paper.

Freshness

Last updated on 2022-04-12.