83 datasets found

Mmbench: Is your multi-modal model an all-around player?

A language model that demonstrates capabilities in processing and generating human-like text.

Mmicl: Empowering vision-language model with multi-modal in-context learning

Prompt Highlighter is a novel paradigm for user-model interactions in multi-modal LLMs, offering output control through a token-level highlighting mechanism.

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

The Conceptual Caption 3M (CC-3M) dataset is a large-scale image captioning dataset.

The COCO-captions dataset contains ∼120k RGB images with text captions.

The dataset used in the paper for text-only image captioning with synthetic pairs.

The BanglaLekhaImageCaptions dataset is a modified version of the dataset introduced in [24]. It contains 9,154 images with two captions for each image.

The MS COCO dataset is a large benchmark for image captioning, containing 328K images with 5 caption descriptions each.

Referring image segmentation aims at localizing all pixels of the visual objects described by a natural language sentence.

GeneIC uses CUB-200 and Oxford-102 datasets for training and testing.

The dataset used in the paper is the Split MS-COCO dataset, which is a comprehensive framework for continual image captioning.

The dataset used in the paper is Conceptual Captions 12M (CC12M) and RedCaps.

The dataset used in the paper is Conceptual Captions 3M (CC3M), Conceptual Captions 12M (CC12M), RedCaps, and LAION-400M.

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 Conceptual Captions 3M dataset is a large-scale image-text dataset used for vision-language pre-training.

The Flickr30k dataset is widely utilized for image caption and image-text retrieval tasks, providing a substantial collection of images with associated captions.

The MSCOCO dataset is a large-scale image captioning dataset, containing 113,287 images with 5,000 validation images and 5,000 test images. The dataset is used for training and...

Conceptual 12m dataset for automatic image captioning