11 datasets found

The dataset is used for image captioning and visual question answering.

The High Quality Image Text Pairs (HQITP-134M) dataset consists of 134 million diverse and high-quality images paired with descriptive captions and titles.

The Winoground dataset consists of 400 items, each containing two image-caption pairs (I0, C0), (I1, C1).

The Conceptual Captions 12M (CC-12M) dataset consists of 12 million diverse and high-quality images paired with descriptive captions and titles.

The dataset used in the paper "Scaling Laws of Synthetic Images for Model Training". The dataset is used for supervised image classification and zero-shot classification tasks.

The dataset used in this paper is a multimodal large language model (LLaMA) dataset, specifically LLaVA-1.5, which consists of 7 billion parameters and is used for multimodal...

The Amazon Berkeley Objects Dataset (ABO) is a public available e-commerce dataset with multiple images per product.

The Visual Genome dataset is a large-scale visual question answering dataset, containing 1.5 million images, each with 15-30 annotated entities, attributes, and relationships.

Large scale datasets [18, 17, 27, 6] boosted text conditional image generation quality. However, in some domains it could be difficult to make such datasets and usually it could...

The Microsoft COCO dataset was used for training and evaluating the CNNs because it has become a standard benchmark for testing algorithms aimed at scene understanding and...

Human Pose Estimation (HPE) aims to estimate the position of each joint point of the human body in a given image. HPE tasks support a wide range of downstream tasks such as...