41 datasets found

A multimodal WBC dataset for WBC classification, consisting of four modalities and five classes.

AVEC2019 DDS is a benchmark dataset for depression detection.

Multimodal sentiment analysis and depression estimation are two important research topics that aim to predict human mental states using multimodal data.

The MUTE dataset is a multimodal dataset for detecting hateful memes.

The MemoSEN dataset is a multimodal dataset for sentiment analysis of Bengali memes.

Visual question answering dataset

Reasoning detection dataset for multimodal large language models

The BabelPic dataset is a multimodal dataset for non-concrete concepts.

Epic Kitchens dataset is a dataset for egocentric vision and action recognition.

Geospatial datasets are diverse, naturally spatiotemporal, and inherently multimodal (composed of two or more distinct signal types or modalities) e.g., satellite/aerial imagery...

The authors present a synthetic Car Pedestrian Interaction (CPI) dataset for evaluating multimodal future predictions.

The ReasonSeg dataset is a benchmark for reasoning segmentation tasks, which demands a nuanced comprehension of intricate queries to accurately pinpoint object regions.

The BraTS 2019 validation and testing datasets are used to evaluate the performance of the proposed segmentation method.

Multimodal brain tumor segmentation challenge (BraTS) aims to evaluate state-of-the-art methods for the segmentation of brain tumors by providing a 3D MRI dataset with ground...

The MulRan dataset is a multimodal range dataset for urban place recognition, containing data collected from a scanning Navtech radar in various weather conditions.

The NTU-RGBD dataset is a large-scale dataset for 3D human activity analysis, containing 56,000 videos and 60 actions performed by 40 people from 80 different views.

Multimodal meme dataset (MultiOFF) for identifying offensive content in image and text.

Multimodal hateful content detection is a challenging task that requires complex reasoning across visual and textual modalities.

The dataset used in the paper is a multimodal learning task for robots.

The dataset used in the paper is a multimodal categorization task using image data and speech signals.