dataset_name stringlengths 2 128 | description stringlengths 1 9.7k | prompt stringlengths 59 185 |
|---|---|---|
Chest x-ray landmark dataset | Set of landmark annotations for JSRT, Montgomery, Shenzhen and a subset of Padchest datasets | Provide a detailed description of the following dataset: Chest x-ray landmark dataset |
Montgomery County X-ray Set | X-ray images in this data set have been acquired from the tuberculosis control program of the Department of Health andHuman Services of Montgomery County, MD, USA. This set contains 138 posterior-anterior x-rays, of which 80 x-rays are normal and 58 x-rays areabnormal with manifestations of tuberculosis. All images are... | Provide a detailed description of the following dataset: Montgomery County X-ray Set |
Shenzhen Hospital X-ray Set | X-ray images in this data set have been collected by Shenzhen No.3 Hospital in Shenzhen, Guangdong providence,China. The x-rays were acquired as part of the routine care at Shenzhen Hospital. The set contains images in JPEG format. There are 326 normal x-raysand 336 abnormal x-rays showing various manifestations of tub... | Provide a detailed description of the following dataset: Shenzhen Hospital X-ray Set |
ARQMath2 - Task 1 | The goal of ARQMath is to advance techniques for mathematical information retrieval, in particular, retrieving answers to mathematical questions (Task 1), and formula retrieval (Task 2).
Using the question posts from Math Stack Exchange, participating systems are given a question or a formula from a question and asked... | Provide a detailed description of the following dataset: ARQMath2 - Task 1 |
ACDC (Adverse Conditions Dataset with Correspondences) | We introduce ACDC, the Adverse Conditions Dataset with Correspondences for training and testing semantic segmentation methods on adverse visual conditions. It comprises a large set of 4006 images which are evenly distributed between fog, nighttime, rain, and snow. Each adverse-condition image comes with a high-quality ... | Provide a detailed description of the following dataset: ACDC (Adverse Conditions Dataset with Correspondences) |
RR | Review-Rebuttal (RR) dataset is introduced to facilitate the study of argument pair extraction in the peer review and rebuttal domain. | Provide a detailed description of the following dataset: RR |
XYSquares | Synthetic dataset intended for benchmarking disentanglement frameworks.
XYSquares is adversarial in nature; the distance between any two observations in the dataset is constant when measured using a pixel-wise distance function. It is usually impossible for VAE frameworks that use pixel-wise losses to disentangle th... | Provide a detailed description of the following dataset: XYSquares |
OpenLane | **OpenLane** is the first real-world and the largest scaled 3D lane dataset to date. The dataset collects valuable contents from public perception dataset [Waymo Open Dataset](/dataset/waymo-open-dataset) and provides lane&closest-in-path object(CIPO) annotation for 1000 segments. In short, OpenLane owns 200K frames an... | Provide a detailed description of the following dataset: OpenLane |
3D Cars | Car CAD models from "3d object detection and viewpoint estimation with a deformable
3d cuboid model" were used to generate the dataset. For each of the 199 car models, the authors generated $64\times64$ color renderings from 24 rotation angles each offset by 15 degrees, as well as from 4 different camera elevations. | Provide a detailed description of the following dataset: 3D Cars |
Physical Audiovisual CommonSense | **PACS** (**Physical Audiovisual CommonSense**) is the first audiovisual benchmark annotated for physical commonsense attributes. PACS contains a total of 13,400 question-answer pairs, involving 1,377 unique physical commonsense questions and 1,526 videos. The dataset provides new opportunities to advance the research ... | Provide a detailed description of the following dataset: Physical Audiovisual CommonSense |
EgoMon | EgoMon Gaze & Video Dataset is an Egocentric (first person) Dataset that consists of 7 videos of 30 minutes, more or less, each one of them.
- 7 videos with the gaze information plotted on them.
- The same videos (without the gaze information plotted on them).
- A total of 13428 images, more or less, that correspond... | Provide a detailed description of the following dataset: EgoMon |
ChangeIt | ChangeIt dataset with more than 2600 hours of video with state-changing actions published at CVPR 2022. | Provide a detailed description of the following dataset: ChangeIt |
SynLiDAR | SynLiDAR is a large-scale synthetic LiDAR sequential point cloud dataset with point-wise annotations. 13 sequences of LiDAR point cloud with around 20k scans (over 19 billion points and 32 semantic classes) are collected from virtual urban cities, suburban towns, neighborhood, and harbor. | Provide a detailed description of the following dataset: SynLiDAR |
CUHK-SYSU-TBPS | CUHK-SYSU-TBPS is a dataset for text-based person search task. | Provide a detailed description of the following dataset: CUHK-SYSU-TBPS |
PRW-TBPS | PRW-TBPS is a dataset for text based person search task. | Provide a detailed description of the following dataset: PRW-TBPS |
VinDr-CXR | **VinDr-CXR** is an open large-scale dataset of chest X-rays with radiologist’s annotations. It's bult from more than 100,000 raw images in DICOM format that were retrospectively collected from the Hospital 108 and the Hanoi Medical University Hospital, two of the largest hospitals in Vietnam. The published dataset con... | Provide a detailed description of the following dataset: VinDr-CXR |
VinDr-PCXR | **VinDr-PCXR** is an open, large-scale pediatric chest X-ray dataset for interpretation of common thoracic diseases in children. The dataset contains 9,125 CXR scans retrospectively collected from a major pediatric hospital in Vietnam between 2020 and 2021. Each scan was manually annotated by a pediatric radiologist wh... | Provide a detailed description of the following dataset: VinDr-PCXR |
TimberSeg 1.0 | The **TimberSeg 1.0** dataset is composed of 220 images showing wood logs in various environments and conditions in Canada. The images are densely annotated with segmentation masks for each log instance, as well as the corresponding bounding box and class label. This dataset aim towards enabling autonomous forestry fo... | Provide a detailed description of the following dataset: TimberSeg 1.0 |
CrossLoc Benchmark Datasets | To study the data-scarcity mitigation for learning-based visual localization methods via sim-to-real transfer, we curate and now present the CrossLoc benchmark datasets—a multimodal aerial sim-to-real data available for flights above nature and urban terrains. Unlike the previous computer vision datasets focusing on lo... | Provide a detailed description of the following dataset: CrossLoc Benchmark Datasets |
Daily load patterns | This data set provides fine-granular statistics on trading traffic generated by six global exchanges over the course of two days in February 2019 for a set of representative feeds and recorded by the systems of vwd Vereinigte Wirtschaftsdienste GmbH (now known as Infront Financial Technology GmbH).
Please note that ... | Provide a detailed description of the following dataset: Daily load patterns |
SerialTrack Particle Image Dataset | This dataset accompanies the linked SerialTrack paper and provides test case data (2D/3D, varying particle density) across a range of synthetic and experimental imaging modalities. Included test cases can be used for further code development, validation of and comparisons for existing particle tracking codes, and/or ev... | Provide a detailed description of the following dataset: SerialTrack Particle Image Dataset |
BrWac2Wiki | This is a dataset for multi-document summarization in Portuguese, what means that it has examples of multiple documents (input) related to human-written summaries (output). In particular, it has entries of multiple related texts from Brazilian websites about a subject, and the summary is the Portuguese Wikipedia lead s... | Provide a detailed description of the following dataset: BrWac2Wiki |
Hello Watt | Hello Watt collects power usage data at a resolution of 30 minutes. To develop and test our disaggregation methods we consider a subsample consisting of power consumption of 5k households with off-peak pricing contracts for one month.
In addition to the type of their water heating, some users also provide such metadat... | Provide a detailed description of the following dataset: Hello Watt |
STEM-ECR | ###Grounding Scientific Entity References in STEM Scholarly Content to Authoritative Encyclopedic and Lexicographic Sources
The STEM ECR v1.0 dataset has been developed to provide a benchmark for the evaluation of scientific entity extraction, classification, and resolution tasks in a domain-independent fashion. It ... | Provide a detailed description of the following dataset: STEM-ECR |
endless forams | This dataset was built based on a subset of foraminifer samples from the Yale Peabody Museum (YPM) Coretop Collection and the Natural History Museum, Lon- don (NHM) Henry A. Buckley Collection. | Provide a detailed description of the following dataset: endless forams |
CronQuestions | CRONQUESTIONS, the Temporal KGQA dataset
consists of two parts: a KG with temporal annotations, and a set of natural language questions requiring temporal reasoning. | Provide a detailed description of the following dataset: CronQuestions |
i2b2 De-identification Dataset | This dataset contains 1304 de-identified longitudinal medical records describing 296 patients. | Provide a detailed description of the following dataset: i2b2 De-identification Dataset |
MATRES | This is the Multi-Axis Temporal RElations for Start-points (i.e., MATRES) dataset | Provide a detailed description of the following dataset: MATRES |
DuLeMon | DuLeMon is a large-scale Chinese Long-term Memory Conversation dataset, which simulates long-term memory conversations and focuses on the ability to actively construct and utilize the user's and the bot's persona in a long-term interaction. DuLeMon contains about 27.5k human-human conversations, 449k utterances, and 12... | Provide a detailed description of the following dataset: DuLeMon |
BigDetection | **BigDetection** is a new large-scale benchmark to build more general and powerful object detection systems. It leverages the training data from existing datasets ([LVIS](/dataset/lvis), [OpenImages](/dataset/openimages-v6) and [Object365](/dataset/objects365)) with carefully designed principles, and curate a larger da... | Provide a detailed description of the following dataset: BigDetection |
MIMIC-IV-ED | MIMIC-IV-ED is a large, freely available database of emergency department (ED) admissions at the Beth Israel Deaconess Medical Center between 2011 and 2019. As of MIMIC-ED v1.0, the database contains 448,972 ED stays. Vital signs, triage information, medication reconciliation, medication administration, and discharge d... | Provide a detailed description of the following dataset: MIMIC-IV-ED |
GD-NLI | This is a set of *debiased* Natural Language Inference (NLI) datasets produced by the paper [Generating Data to Mitigate Spurious Correlations in Natural Language Inference Datasets](https://arxiv.org/abs/2203.12942). The datasets are constructed by augmenting SNLI or MNLI with data samples that are *generated to miti... | Provide a detailed description of the following dataset: GD-NLI |
MIMIC-IV | Retrospectively collected medical data has the opportunity to improve patient care through knowledge discovery and algorithm development. Broad reuse of medical data is desirable for the greatest public good, but data sharing must be done in a manner which protects patient privacy.
The Medical Information Mart for ... | Provide a detailed description of the following dataset: MIMIC-IV |
Dataset of Distribution Transformers at Cauca Department (Colombia) | Dataset contains 16.000 electric power distribution transformers from Cauca Department (Colombia).
They are distributed in rural and urban areas of 42 municipalities. The information covers
2019 and 2020 years, has 6 categorical variables and 5 continuous variables. First ones correspond to:
location, self-protected... | Provide a detailed description of the following dataset: Dataset of Distribution Transformers at Cauca Department (Colombia) |
V3C1 | The dataset has been designed to represent true web videos in the wild, with good visual quality and diverse content characteristics, and will serve as evaluation basis for the Video Browser Showdown 2019-2021 and TREC Video Retrieval (TRECVID) Ad-Hoc Video Search tasks 2019-2021. The dataset comes with a shot segmenta... | Provide a detailed description of the following dataset: V3C1 |
IACC.3 | The IACC.3 dataset is approximately 4600 Internet Archive videos (144 GB, 600 h) with Creative Commons licenses in MPEG-4/H.264 format with duration ranging from 6.5 min to 9.5 min and a mean duration of almost 7.8 min. Most videos will have some metadata provided by the donor available e.g., title, keywords, and descr... | Provide a detailed description of the following dataset: IACC.3 |
Rope3D | **Roadside Perception 3D** (**Rope3D**) is a dataset for autonomous driving and monocular 3D object detection task consisting of 50k images and over 1.5M 3D objects in various scenes, which are captured under different settings including various cameras with ambiguous mounting positions, camera specifications, viewpoin... | Provide a detailed description of the following dataset: Rope3D |
ATLANTIS | **ATLANTIS** is a benchmark for semantic segmentation of waterbody images. This dataset covers a wide range of natural waterbodies such as sea, lake, river and man-made (artificial) water-related structures such as dam, reservoir, canal, and pier. ATLANTIS includes 5,195 pixel-wise annotated images split to 3,364 train... | Provide a detailed description of the following dataset: ATLANTIS |
UDE-Office-Home | Different from the setting of domain adaptation which uses all labeled source and unlabeled target domain examples for training, domain examples should be divided into two disjoint parts: training and test. UDE-Office-Home is built from Office-Home, so the performance of domain-adapted or domain-expanded models on th... | Provide a detailed description of the following dataset: UDE-Office-Home |
UDE-DomainNet | Different from the setting of domain adaptation which uses all labeled source and unlabeled target domain examples for training, domain examples should be divided into two disjoint parts: training and test. UDE-DomainNet is built from DomainNet, so the performance of domain-adapted or domain-expanded models on the so... | Provide a detailed description of the following dataset: UDE-DomainNet |
PlotQA | PlotQA is a VQA dataset with 28.9 million question-answer pairs grounded over 224,377 plots on data from real-world sources and questions based on crowd-sourced question templates.
Existing synthetic datasets (FigureQA, DVQA) for reasoning over plots do not contain variability in data labels, real-valued data, or comp... | Provide a detailed description of the following dataset: PlotQA |
IAM Dataset | We introduce a large and comprehensive dataset to facilitate the study of several essential AM tasks in the debating system. In our work, we first review the existing subtasks (claim extraction, stance classification, evidence extraction), and then propose two integrated argument mining tasks: claim extraction with sta... | Provide a detailed description of the following dataset: IAM Dataset |
AWS Documentation | We present the AWS documentation corpus, an open-book QA dataset, which contains 25,175 documents along with 100 matched questions and answers. These questions are inspired by the author's interactions with real AWS customers and the questions they asked about AWS services. The data was anonymized and aggregated. All q... | Provide a detailed description of the following dataset: AWS Documentation |
TEM nanowire morphologies for classification and segmentation | TEM image dataset containing four nanowire morphologies of bio-derived protein nanowires and synthetic peptide nanowires.
The peptide / protein nanowires used in this study were synthesized and imaged by Brian Montz in Prof. Todd Emrick's research group at the Department of Polymer Science and Engineering Department... | Provide a detailed description of the following dataset: TEM nanowire morphologies for classification and segmentation |
Battery test data - fast formation study | Forty prismatic lithium-ion pouch cells were built at the University of Michigan Battery Laboratory. The cells have a nominal capacity of 2.36Ah and comprise a NCM111 cathode and graphite anode. Cells were formed using two different formation protocols: "fast formation" and "baseline formation". After formation, cells ... | Provide a detailed description of the following dataset: Battery test data - fast formation study |
TRECVID-AVS16 (IACC.3) | Internet Archive videos (IACC.3) under Creative Commons licenses. The test video collection for TRECVID-AVS2016-TRECVID-AVS2018 contains 335,944 web video clips (600hr). | Provide a detailed description of the following dataset: TRECVID-AVS16 (IACC.3) |
TRECVID-AVS17 (IACC.3) | Internet Archive videos (IACC.3) under Creative Commons licenses. The test video collection for TRECVID-AVS2016-TRECVID-AVS2018 contains 335,944 web video clips (600hr). | Provide a detailed description of the following dataset: TRECVID-AVS17 (IACC.3) |
TRECVID-AVS18 (IACC.3) | Internet Archive videos (IACC.3) under Creative Commons licenses. The test video collection for TRECVID-AVS2016-TRECVID-AVS2018 contains 335,944 web video clips (600hr). | Provide a detailed description of the following dataset: TRECVID-AVS18 (IACC.3) |
TRECVID-AVS19 (V3C1) | The dataset has been designed to represent true web videos in the wild, with good visual quality and diverse content characteristics, The test video collection for TRECVID-AVS2019-TRECVID-AVS2021, which contains 1,082,649 web video clips, with even more diverse content, no predominant characteristics and low self-simi... | Provide a detailed description of the following dataset: TRECVID-AVS19 (V3C1) |
TRECVID-AVS20 (V3C1) | The dataset has been designed to represent true web videos in the wild, with good visual quality and diverse content characteristics, The test video collection for TRECVID-AVS2019-TRECVID-AVS2021, which contains 1,082,649 web video clips, with even more diverse content, no predominant characteristics and low self-simi... | Provide a detailed description of the following dataset: TRECVID-AVS20 (V3C1) |
TRECVID-AVS21 (V3C1) | The dataset has been designed to represent true web videos in the wild, with good visual quality and diverse content characteristics, The test video collection for TRECVID-AVS2019-TRECVID-AVS2021, which contains 1,082,649 web video clips, with even more diverse content, no predominant characteristics and low self-simi... | Provide a detailed description of the following dataset: TRECVID-AVS21 (V3C1) |
RealMCVSR | Our RealMCVSR dataset provides real-world HD video triplets concurrently recorded by Apple iPhone 12 Pro Max equipped with triple cameras having fixed focal lengths: ultra-wide (30mm), wide-angle (59mm), and telephoto (147mm). To concurrently record video triplets, we built an iOS app that provides full control over ex... | Provide a detailed description of the following dataset: RealMCVSR |
ActorShift | **ActorShift** is a dataset where the domain shift comes from the change in actor species: we use humans in the source domain and animals in the target domain. This causes large variances in the appearance and motion of activities. For the corresponding dataset we select 1,305 videos of 7 human activity classes from Ki... | Provide a detailed description of the following dataset: ActorShift |
Niramai Oncho Dataset | Onchocerciasis is causing blindness in over half a million people in the world today. Drug development for the disease is crippled as there is no way of measuring effectiveness of the drug without an invasive procedure. Drug efficacy measurement through assessment of viability of onchocerca worms requires the patients ... | Provide a detailed description of the following dataset: Niramai Oncho Dataset |
SEL | The semantic line (SEL) dataset contains 1,750 outdoor images in total, which are split into 1,575 training and 175 testing images. Each semantic line is annotated by the coordinates of the two end-points on an image boundary. If an image has a single dominant line, it is set as the ground truth primary semantic line. ... | Provide a detailed description of the following dataset: SEL |
Persian Preschool Cognition Speech | Data collection was conducted by asking some adults from social media and some students from an elementary school to participate in our experiment.
Table.1 shows the number of data gathered for recognizing each color. Due to the fact that two words are used for black in Persian, the number of black samples is more. I... | Provide a detailed description of the following dataset: Persian Preschool Cognition Speech |
MedMCQA | **MedMCQA** is a large-scale, Multiple-Choice Question Answering (MCQA) dataset designed to address real-world medical entrance exam questions.
MedMCQA has more than 194k high-quality AIIMS & NEET PG entrance exam MCQs covering 2.4k healthcare topics and 21 medical subjects are collected with an average token length... | Provide a detailed description of the following dataset: MedMCQA |
InstaOrder | InstaOrder can be used to understand the geometrical relationships of instances in an image. The dataset consists of 2.9M annotations of geometric orderings for class-labeled instances in 101K natural scenes. The scenes were annotated by 3,659 crowd-workers regarding (1) occlusion order that identifies occluder/occlude... | Provide a detailed description of the following dataset: InstaOrder |
GDA | The gene-disease associations corpus contains 30,192 titles and abstracts from PubMed articles that have been automatically labelled for genes, diseases and gene-disease associations via distant supervision. The test set is comprised of 1000 of these examples. It is common to hold out a random 20% of the examples in th... | Provide a detailed description of the following dataset: GDA |
Relative Human | Relative Human (RH) contains multi-person in-the-wild RGB images with rich human annotations, including:
Depth layers: relative depth relationship/ordering between all people in the image.
Age group classfication: adults, teenagers, kids, babies.
Others: Genders, Bounding box, 2D pose. | Provide a detailed description of the following dataset: Relative Human |
SpokenSTS | Spoken versions of the Semantic Textual Similarity dataset for testing semantic sentence level embeddings. Contains thousands of sentence pairs annotated by humans for semantic similarity. The spoken sentences can be used in sentence embedding models to test whether your model learns to capture sentence semantics. All ... | Provide a detailed description of the following dataset: SpokenSTS |
NAS Dataset for DIP | Dataset for our CVPR paper: "ISNAS-DIP: Image-Specific Neural Architecture Search for Deep Image Prior". | Provide a detailed description of the following dataset: NAS Dataset for DIP |
CNN Filter DB | A database of over 1.4 billion 3x3 convolution filters extracted from hundreds of diverse CNN models with relevant meta information. | Provide a detailed description of the following dataset: CNN Filter DB |
Heavy Snowfall | We introduce an object detection dataset in challenging adverse weather conditions covering 12000 samples in real-world driving scenes and 1500 samples in controlled weather conditions within a fog chamber. The dataset includes different weather conditions like fog, snow, and rain and was acquired by over 10,000 km of ... | Provide a detailed description of the following dataset: Heavy Snowfall |
Light Snowfall | We introduce an object detection dataset in challenging adverse weather conditions covering 12000 samples in real-world driving scenes and 1500 samples in controlled weather conditions within a fog chamber. The dataset includes different weather conditions like fog, snow, and rain and was acquired by over 10,000 km of ... | Provide a detailed description of the following dataset: Light Snowfall |
Clear Weather | We introduce an object detection dataset in challenging adverse weather conditions covering 12000 samples in real-world driving scenes and 1500 samples in controlled weather conditions within a fog chamber. The dataset includes different weather conditions like fog, snow, and rain and was acquired by over 10,000 km of ... | Provide a detailed description of the following dataset: Clear Weather |
CORD | OCR is inevitably linked to NLP since its final output is in text. Advances in document intelligence are driving the need for a unified technology that integrates OCR with various NLP tasks, especially semantic parsing. Since OCR and semantic parsing have been studied as separate tasks so far, the datasets for each tas... | Provide a detailed description of the following dataset: CORD |
Soil and Plant X-ray CT data with semantic annotations | Leaves from genetically unique Juglans regia plants were scanned using X-ray micro-computed tomography (microCT) on the X-ray μCT beamline (8.3.2) at the Advanced Light Source (ALS) in Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA USA).
Soil samples were collected in Fall of 2017 from the riparian oak f... | Provide a detailed description of the following dataset: Soil and Plant X-ray CT data with semantic annotations |
NILoc | IMU, WiFi data along with aligned Visual SLAM groundtruth locations from a smartphone carried during natural human motion | Provide a detailed description of the following dataset: NILoc |
OPD Dataset | The link includes both our OPDSynth and OPDReal dataset. For OPDSynth, we select objects with openable parts from an existing dataset of articulated 3D models PartNet-Mobility. For OPDReal, we reconstruct 3D polygonal meshes for articulated objects in real indoor environments and annotate their parts and articulation i... | Provide a detailed description of the following dataset: OPD Dataset |
NKL | NKL (short for NanKai Lines) is a dataset for semantic line detection. Semantic lines are meaningful line structures that outline the conceptual structure of natural images. The NKL dataset contains 5,000 images of various scenes. Each of these images is annotated by multiple skilled human annotators. The dataset is s... | Provide a detailed description of the following dataset: NKL |
MedQA-USMLE | Multiple choice question answering based on the United States Medical License Exams (USMLE). The dataset is collected from the professional medical board exams. It covers three languages: English, simplified Chinese, and traditional Chinese, and contains 12,723, 34,251, and 14,123 questions for the three languages, res... | Provide a detailed description of the following dataset: MedQA-USMLE |
CurveLanes | CurveLanes is a new benchmark lane detection dataset with 150K lanes images for difficult scenarios such as curves and multi-lanes in traffic lane detection. It is collected in real urban and highway scenarios in multiple cities in China. It is the largest lane detection dataset so far and establishes a more challengin... | Provide a detailed description of the following dataset: CurveLanes |
HC-STVG1 | The newly proposed HC-STVG task aims to localize the target person spatio-temporally in an untrimmed video. For this task, we collect a new benchmark dataset, which has spatio temporal annotations related to the target persons in complex multi-person scenes, together with full interaction and rich action information. | Provide a detailed description of the following dataset: HC-STVG1 |
HC-STVG2 | We have added data and cleaned the labels in HC-STVG to build the HC-STVG2.0. While the original database contained 5660 videos, the new database has been re-annotated and modified and now contains 16,000 + videos for this challenge. | Provide a detailed description of the following dataset: HC-STVG2 |
FairytaleQA | **FairytaleQA** is a dataset focusing on narrative comprehension of kindergarten to eighth-grade students. Annotated by educational experts based on an evidence-based theoretical framework, FairytaleQA consists of 10,580 explicit and implicit questions derived from 278 children-friendly story narratives, covering seven... | Provide a detailed description of the following dataset: FairytaleQA |
NTIC Screening Dataset | In the last two years, millions of lives have been lost due to COVID-19. Despite the vaccination programmes for a year, hospitalization rates and deaths are still high due to the new variants of COVID-19. Stringent guidelines and COVID-19 screening measures such as temperature check and mask check at all public places ... | Provide a detailed description of the following dataset: NTIC Screening Dataset |
LARQS | Word embedding is a modern distributed word representations approach widely used in many natural language processing tasks. Converting the vocabulary in a legal document into a word embedding model facilitates subjecting legal documents to machine learning, deep learning, and other algorithms and subsequently performin... | Provide a detailed description of the following dataset: LARQS |
NightCity | The largest real-world night-time semantic segmentation dataset with pixel-level labels. | Provide a detailed description of the following dataset: NightCity |
ShipsEar | This contribution presents a database of underwater sounds produced by vessels of various types. Besides sound recordings, the database contains details of the conditions for obtaining each recording: type of vessel, location of the recording equipment, weather conditions, etc. For its realization, a methodology for re... | Provide a detailed description of the following dataset: ShipsEar |
TrojVQA | A collection of 840 pretrained VQA models which may be regular “clean” models or malicious “backdoored” models which have been trained to include a secret backdoor trigger and behavior. This collection includes models with traditional single-key backdoors as well as Dual-Key Multimodal Backdoors.
For more information... | Provide a detailed description of the following dataset: TrojVQA |
SEN | SEN is a novel publicly available human-labelled dataset for training and testing machine learning algorithms for the problem of entity level sentiment analysis of political news headlines.
Dataset consists of 3819 human-labelled political news headlines coming from several major on-line media outlets in English and... | Provide a detailed description of the following dataset: SEN |
SeaDronesSee | SeaDronesSee is a large-scale data set aimed at helping develop systems for Search and Rescue (SAR) using Unmanned Aerial Vehicles (UAVs) in maritime scenarios. Building highly complex autonomous UAV systems that aid in SAR missions requires robust computer vision algorithms to detect and track objects or persons of in... | Provide a detailed description of the following dataset: SeaDronesSee |
DGTA-VisDrone | Object Detection data set created from the engine DeepGTAV, which is based on the video game GTAV. Part of the three data sets proposed in the paper. This data set is motivated from the VisDrone data set with almost the same classes. | Provide a detailed description of the following dataset: DGTA-VisDrone |
DGTA-SeaDronesSee | Object Detection data set created from the engine DeepGTAV, which is based on the video game GTAV. Part of the three data sets proposed in the paper. This data set is motivated from the SeaDronesSee dataset with almost the same classes. | Provide a detailed description of the following dataset: DGTA-SeaDronesSee |
DGTA-Cattle | Object Detection data set created from the engine DeepGTAV, which is based on the video game GTAV. Part of the three data sets proposed in the paper. This data set is motivated from the Cattle dataset with almost the same classes. | Provide a detailed description of the following dataset: DGTA-Cattle |
Cattle | Cattle data set, which was introduced in a paper. We (not the authors) created a train-val-test split. | Provide a detailed description of the following dataset: Cattle |
Pistachio Image Dataset | Citation Request :
1. OZKAN IA., KOKLU M. and SARACOGLU R. (2021). Classification of Pistachio Species Using Improved K-NN Classifier. Progress in Nutrition, Vol. 23, N. 2, pp. DOI:10.23751/pn.v23i2.9686. (Open Access) https://www.mattioli1885journals.com/index.php/progressinnutrition/article/view/9686/9178
ABSTRA... | Provide a detailed description of the following dataset: Pistachio Image Dataset |
SLNET | **SLNET** is collection of third party Simulink models. It is curated via mining open source repository (GitHub and Matlab Central) using SLNET-Miner (https://github.com/50417/SLNet_Miner). | Provide a detailed description of the following dataset: SLNET |
SUN-SEG-Easy (Unseen) | The SUN-SEG dataset is a high-quality per-frame annotated VPS dataset, which includes 158,690 frames from the famous SUN dataset. It extends the labels with diverse types, i.e., object mask, boundary, scribble, polygon, and visual attribute. It also introduces the pathological information from the original SUN dataset,... | Provide a detailed description of the following dataset: SUN-SEG-Easy (Unseen) |
Example EPCIS Event Chain | This is an example data set for a hypothetical electronic products supply network.
The supply network consists of six actors. A simple electronic product is assembled by
Manufacturer C with components from Supplier A and Supplier B. The product is sold to
consumers by Retailer D or Retailer E. Finally, at the end ... | Provide a detailed description of the following dataset: Example EPCIS Event Chain |
P-DukeMTMC-reID | P-DukeMTMC-reID is a modified version based on DukeMTMC-reID dataset. There are 12,927 images (665 identifies) in training set, 2,163 images (634 identities) for querying and 9,053 images in the gallery set. | Provide a detailed description of the following dataset: P-DukeMTMC-reID |
Occluded-DukeMTMC | Occluded-DukeMTMC contains 15,618 training images, 17,661 gallery images, and 2,210 occluded query images. The experiment results on Occluded-DukeMTMC will demonstrate the superiority of our method in Occluded Person Re-ID problems, let alone that our method does not need any manually cropping procedure as pre-process. | Provide a detailed description of the following dataset: Occluded-DukeMTMC |
SUN-SEG-Hard (Unseen) | The SUN-SEG dataset is a high-quality per-frame annotated VPS dataset, which includes 158,690 frames from the famous SUN dataset. It extends the labels with diverse types, i.e., object mask, boundary, scribble, polygon, and visual attribute. It also introduces the pathological information from the original SUN dataset,... | Provide a detailed description of the following dataset: SUN-SEG-Hard (Unseen) |
FoCus | We introduce a new dataset, called FoCus, that supports
knowledge-grounded answers that reflect user’s persona. One
of the situations in which people need different types of
knowledge, based on their preferences, occurs when they
travel around the world. | Provide a detailed description of the following dataset: FoCus |
CICERO | **CICERO** contains 53,000 inferences for five commonsense dimensions -- cause, subsequent event, prerequisite, motivation, and emotional reaction -- collected from 5600 dialogues. It involves two challenging generative and multi-choice alternative selection tasks for the state-of-the-art NLP models to solve. Download ... | Provide a detailed description of the following dataset: CICERO |
FEMNIST | See paper:
Caldas, Sebastian, et al. "Leaf: A benchmark for federated settings." arXiv preprint arXiv:1812.01097 (2018). | Provide a detailed description of the following dataset: FEMNIST |
L3DAS22 | # L3DAS22: MACHINE LEARNING FOR 3D AUDIO SIGNAL PROCESSING
This dataset supports the L3DAS22 IEEE ICASSP Gand Challenge. The challenge is supported by a [Python API](https://github.com/l3das/L3DAS22) that facilitates the dataset download and preprocessing, the training and evaluation of the baseline models and the r... | Provide a detailed description of the following dataset: L3DAS22 |
MS-FIMU | Open Dataset: Mobility Scenario FIMU
* An open, multidimensional (6 categorical attributes), and synthetic dataset of faked virtual humans generated by an optimization approach applied to a real-life call-detail-records-based anonymized database.
* The original database is from a mobile network operator in France (... | Provide a detailed description of the following dataset: MS-FIMU |
RoomEnv-v0 | # The Room environment - v0
[There is a newer version, v1](../README.md)
We have released a challenging [OpenAI Gym](https://www.gymlibrary.dev/) compatible
environment. The best strategy for this environment is to have both episodic and semantic
memory systems. See the [paper](https://arxiv.org/abs/2204.01611)... | Provide a detailed description of the following dataset: RoomEnv-v0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.