19,997 machine learning datasets
19,997 dataset results
The DISRPT 2021 shared task, co-located with CODI 2021 at EMNLP, introduces the second iteration of a cross-formalism shared task on discourse unit segmentation and connective detection, as well as the first iteration of a cross-formalism discourse relation classification task.
MVHand is a new multi-view hand posture dataset to obtain complete 3D point clouds of the hand in the real world.
SaL-Lightning is a dataset for research in the field of Search as Learning. It contains detailed recordings, pre- and post-knowledge assessments of 114 participants, interaction data on real-world search behavior, as well as resource features of a user study. This data diversity has the potential to help researchers answer diverse questions tied to the entire online learning framework, from individual psychological aspects, over usability tests and data visualization over retrieval and ranking issues existing in the technology that enables this process.
KIND is an Italian dataset for Named-Entity Recognition. It contains more than one million tokens with the annotation covering three classes: persons, locations, and organizations. Most of the dataset (around 600K tokens) contains manual gold annotations in three different domains: news, literature, and political discourses.
HSPACE (Human-SPACE) is a large-scale photo-realistic dataset of animated humans placed in complex synthetic indoor and outdoor environments. For all frames the dataset provides 3d pose and shape ground truth, as well as other rich image annotations including human segmentation, body part localisation semantics, and temporal correspondences.
LOOK is a large-scale dataset for eye contact detection in the wild, which focuses on diverse and unconstrained scenarios for real-world generalization. The dataset focuses on real-world scenarios for autonomous vehicles with no control over the environment or the distance of pedestrians
ES-ImageNet is a large-scale event-stream dataset for SNNs and neuromorphic vision. It consists of about 1.3 M samples converted from ILSVRC2012 in 1000 different categories. ES-ImageNet is dozens of times larger than other neuromorphic classification datasets at present and completely generated by the software
This is a high-quality large-scale Night Object Detection (NOD) dataset of outdoor images targeting low-light object detection. The dataset contains more than 7K images and 46K annotated objects (with bounding boxes) that belong to classes: person, bicycle, and car. The photos were taken on the streets at evening hours, and thus all images present low-light conditions to a varying degree of severity.
FFHQ-Text is a small-scale face image dataset with large-scale facial attributes, designed for text-to-face generation & manipulation, text-guided facial image manipulation, and other vision-related tasks. This dataset is an extension of the NVIDIA Flickr-Faces-HQ Dataset (FFHQ), which is the selected top 760 female FFHQ images that only contain one complete human face.
WebUAV-3M is a new million-scale Unmanned Aerial Vehicle (UAV) tracking benchmark consisting of 4,485 videos with more than 3M frames from the Internet. An efficient and scalable Semi-Automatic Target Annotation (SATA) pipeline is devised to label the tremendous WebUAV-3M in every frame. The densely bounding box annotated WebUAV-3M one of the largest public UAV tracking benchmark.
Semi-Structured Explanations for COPA (COPA-SSE) is a new crowdsourced dataset of 9,747 semi-structured, English common sense explanations for COPA questions. The explanations are formatted as a set of triple-like common sense statements with ConceptNet relations but freely written concepts. This semi-structured format strikes a balance between the high quality but low coverage of structured data and the lower quality but high coverage of free-form crowdsourcing. Each explanation also includes a set of human-given quality ratings. With their familiar format, the explanations are geared towards commonsense reasoners operating on knowledge graphs and serve as a starting point for ongoing work on improving such systems.
EventNarrative is a knowledge graph-to-text dataset from publicly available open-world knowledge graphs. EventNarrative consists of approximately 230,000 graphs and their corresponding natural language text.
A large-scale video portrait dataset that contains 291 videos from 23 conference scenes with 14K frames. This dataset contains various teleconferencing scenes, various actions of the participants, interference of passers-by and illumination change.
The dataset has been generated using Town 1 and Town 2 of CARLA Simulator. The dataset consists of 50 camera configurations with each town having 25 configurations. The parameters modified for generating the configurations include f ov, x, y, z, pitch, yaw, and roll. Here, f ov is the field of view, (x, y, z) is the translation while (pitch, yaw, and roll) is the rotation between the cameras. The total number of image pairs is 1,23,017, out of which 58,596 belong to Town 1 while 64,421 belong to Town 2, the difference in the number of images is due to the length of the tracks.
We present a dataset, DANFEVER, intended for claim verification in Danish. The dataset builds upon the task framing of the FEVER fact extraction and verification challenge. DANFEVER can be used for creating models for detecting mis- & disinformation in Danish as well as for verification in multilingual settings.
QALD-9-Plus Dataset Description QALD-9-Plus is the dataset for Knowledge Graph Question Answering (KGQA) based on well-known QALD-9.
Wiki-Convert is a 900,000+ sentences dataset of precise number annotations from English Wikipedia. It relies on Wiki contributors' annotations in the form of a {{Convert}} template.
DELAUNAY is a dataset of abstract paintings and non-figurative art objects labelled by the artists' names. This dataset provides a middle ground between natural images and artificial patterns and can thus be used in a variety of contexts, for example to investigate the sample efficiency of humans and artificial neural networks.
Medical Question Pairs (MQP) Dataset This repository contains a dataset of 3048 similar and dissimilar medical question pairs hand-generated and labeled by Curai's doctors. The dataset is described in detail in our paper.
This Dataset consists of 2120 sequences of binary masks of pedestrians. The sequence length varies between 2-710. For details, we refer to our paper. It is based on the original KITTI Segmentation challenge which can be found at https://www.vision.rwth-aachen.de/page/mots