10 datasets found

A new freely available human-human dialogue data set for interactive learning of visually grounded word meanings through ostensive definition by a tutor to a learner.

A dataset for visual grounding on point clouds, focusing on relation modeling.

The SWiG dataset is a large-scale visual grounding dataset, where the task is to predict the object in an image.

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

SpeechCLIP is a novel framework to integrate speech SSL models with a pre-trained vision and language model.

The RefCOCOg dataset is a reconstructed dataset of the MS-COCO dataset, containing 85,474 referring expressions for 54,822 objects in 26,711 images.

The dataset used in the paper is a benchmark for referring expression grounding, containing 142,210 referring expressions for 50,000 referents in 19,994 images.

VGDiffZero is a zero-shot visual grounding framework that leverages pre-trained text-to-image diffusion models' vision-language alignment abilities.

Visual Grounding is a task that aims to locate a target object according to a natural language expression. The dataset used in this paper is RefCOCO, RefCOCO+, and RefCOCOg.

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.