dataset_name stringlengths 2 128 | description stringlengths 1 9.7k | prompt stringlengths 59 185 |
|---|---|---|
MetaGraspNet 1 | There has been increasing interest in smart factories powered by robotics systems to tackle repetitive, laborious tasks. One particular impactful yet challenging task in robotics-powered smart factory applications is robotic grasping: using robotic arms to grasp objects autonomously in different settings.
Robotic grasp... | Provide a detailed description of the following dataset: MetaGraspNet 1 |
MetaGraspNet 2 | There has been increasing interest in smart factories powered by robotics systems to tackle repetitive, laborious tasks. One particular impactful yet challenging task in robotics-powered smart factory applications is robotic grasping: using robotic arms to grasp objects autonomously in different settings.
Robotic grasp... | Provide a detailed description of the following dataset: MetaGraspNet 2 |
MetaGraspNet 3 | There has been increasing interest in smart factories powered by robotics systems to tackle repetitive, laborious tasks. One particular impactful yet challenging task in robotics-powered smart factory applications is robotic grasping: using robotic arms to grasp objects autonomously in different settings.
Robotic grasp... | Provide a detailed description of the following dataset: MetaGraspNet 3 |
MetaGraspNet 4 | There has been increasing interest in smart factories powered by robotics systems to tackle repetitive, laborious tasks. One particular impactful yet challenging task in robotics-powered smart factory applications is robotic grasping: using robotic arms to grasp objects autonomously in different settings.
Robotic grasp... | Provide a detailed description of the following dataset: MetaGraspNet 4 |
MetaGraspNet 5 | There has been increasing interest in smart factories powered by robotics systems to tackle repetitive, laborious tasks. One particular impactful yet challenging task in robotics-powered smart factory applications is robotic grasping: using robotic arms to grasp objects autonomously in different settings.
Robotic grasp... | Provide a detailed description of the following dataset: MetaGraspNet 5 |
Multiview Manipulation Data | Accompanying expert data and trained models for 2021 IROS paper on Multiview Manipulation. | Provide a detailed description of the following dataset: Multiview Manipulation Data |
GMVD | The GMVD dataset consists of synthetic scenes captured using the GTA-V and Unity graphics engines. The dataset covers a variety of scenes, along with different conditions including day time variations (morning, afternoon, evening, night) and weather variations (sunny, cloudy, rainy, snowy). The purpose of the dataset i... | Provide a detailed description of the following dataset: GMVD |
NLC2CMD | The NLC2CMD Competition hosted at NeurIPS 2020 aimed to bring the power of natural
language processing to the command line. Participants were tasked with building models
that can transform descriptions of command line tasks in English to their Bash syntax. | Provide a detailed description of the following dataset: NLC2CMD |
2018 n2c2 (Track 2) - Adverse Drug Events and Medication Extraction | Abstract
Objective
This article summarizes the preparation, organization, evaluation, and results of Track 2 of the 2018 National NLP Clinical Challenges shared task. Track 2 focused on extraction of adverse drug events (ADEs) from clinical records and evaluated 3 tasks: concept extraction, relation classification, a... | Provide a detailed description of the following dataset: 2018 n2c2 (Track 2) - Adverse Drug Events and Medication Extraction |
SPARTQA - | We take advantage of the ground truth of NLVR images, design CFGs to generate stories, and use spatial reasoning rules to ask and answer spatial reasoning questions. This automatically generated data is called SpaRTQA. https://aclanthology.org/2021.naacl-main.364/ | Provide a detailed description of the following dataset: SPARTQA - |
Moon Phases | Dates with Moon phases extended days until next phase (1992/1/4 to 2027/12/20)
Incorporate lunar data to your research.
The moon affects multiple physical things on the earth, such as the ocean tides, the behavior of living organisms as well as humans
Moon Phases data
0 = New Moon
1 = first day after New Moo... | Provide a detailed description of the following dataset: Moon Phases |
CLIPS | CLIPS, ovvero Corpora e Lessici dell'Italiano Parlato e Scritto, è uno degli otto progetti (Progetto n. 2) del Cluster C18 "LINGUISTICA COMPUTAZIONALE: RICERCHE MONOLINGUI E MULTILINGUI" (Legge 488), finanziato dal Ministero dell'Istruzione, dell'Università e della Ricerca (MIUR). | Provide a detailed description of the following dataset: CLIPS |
Phone call network for 2 years in a Euro country | We employ a nationwide phone call dataset from Jan. 2015 to Dec. 2016.
The *log* interaction duration and *log* interaction frequency in each phase (intermediate results) are both provided. Currently, we upload the Results folder to Google Drive.
(https://drive.google.com/drive/folders/1h4rHZvzzQO7niYMelbzToJZernOij1... | Provide a detailed description of the following dataset: Phone call network for 2 years in a Euro country |
RodoSol-ALPR | This dataset, called RodoSol-ALPR dataset, contains 20,000 images captured by static cameras located at pay tolls owned by the *Rodovia do Sol* (RodoSol) concessionaire, which operates 67.5 kilometers of a highway (ES-060) in the Brazilian state of Espírito Santo.
There are images of different types of vehicles (e.g... | Provide a detailed description of the following dataset: RodoSol-ALPR |
LTFT | Dataset originally conceived for multi-face tracking/detection for highly crowded scenarios. In these scenarios, the face is the only part that can be used to track the individuals.
All our videos present novel crowd scenes recorded at near-eye level, where faces are visible enough to be analysed at the microscopic ... | Provide a detailed description of the following dataset: LTFT |
IMS Bearing Dataset | Bearing acceleration data from three run-to-failure experiments on a loaded shaft. The data set was provided by the Center for Intelligent Maintenance Systems (IMS), University of Cincinnati. | Provide a detailed description of the following dataset: IMS Bearing Dataset |
PRONOSTIA Bearing Dataset | The PRONOSTIA (also called FEMTO) bearing dataset consists of 17 accelerated run-to-failures on a small bearing test rig. Both acceleration and temperature data was collected for each experiment.
The dataset was used in the 2012 IEEE Prognostic Challenge. The dataset is from FEMTO-ST Institute in France. | Provide a detailed description of the following dataset: PRONOSTIA Bearing Dataset |
LSA64 | The sign database for the Argentinian Sign Language, created with the goal of producing a dictionary for LSA and training an automatic sign recognizer, includes 3200 videos where 10 non-expert subjects executed 5 repetitions of 64 different types of signs. Signs were selected among the most commonly used ones in the LS... | Provide a detailed description of the following dataset: LSA64 |
Makeup216 | Makeup216 contains a variety and representation of logo (captured from the real world) and is among the largest and most complex logo datasets in the field. It comprises of 216 logos and 157 brands, including 10,019 images and 37,018 annotated logo objects. | Provide a detailed description of the following dataset: Makeup216 |
MVHand | MVHand is a new multi-view hand posture dataset to obtain complete 3D point clouds of the hand in the real world. | Provide a detailed description of the following dataset: MVHand |
Wikidated 1.0 | **Wikidated 1.0** is a dataset of Wikidata's full revision history, which encodes changes between Wikidata revisions as sets of deletions and additions of RDF triples. It constitutes one of the first large datasets of an evolving knowledge graph, a recently emerging research subject in the Semantic Web community. | Provide a detailed description of the following dataset: Wikidated 1.0 |
Drosophila Immunity Time-Course Data | The data used for all results in this paper can be found [here](https://github.com/sara-venkatraman/Bayesian-Gene-Dynamics/tree/master/Data). This directory contains:
* `GeneData.csv`: Contains temporal gene expression measurements for 1735 genes at 17 time points. Measurements are provided as the $\log_2$-fold chan... | Provide a detailed description of the following dataset: Drosophila Immunity Time-Course Data |
VGG-Sound Sync | **VGG-Sound Sync** is an audio-visual synchronisation benchmark based on videos collected from YouTube. VGG-Sound Sync contains over 100k video clips, spanning 160 classes and can be downloaded [here](https://www.robots.ox.ac.uk/~vgg/research/avs/data/vggsoundsync.csv).
Note, only the test clips are included here, p... | Provide a detailed description of the following dataset: VGG-Sound Sync |
BRATS21 | The RSNA-ASNR-MICCAI BraTS 2021 challenge utilizes multi-institutional pre-operative baseline multi-parametric magnetic resonance imaging (mpMRI) scans, and focuses on the evaluation of state-of-the-art methods for (Task 1) the segmentation of intrinsically heterogeneous brain glioblastoma sub-regions in mpMRI scans. F... | Provide a detailed description of the following dataset: BRATS21 |
MetaVD | MetaVD is a *Meta Video Dataset* for enhancing human action recognition datasets.
It provides human-annotated relationship labels between action classes across human action recognition datasets.
MetaVD is proposed in the following paper:
**Yuya Yoshikawa, Yutaro Shigeto, and Akikazu Takeuchi. "MetaVD: A Meta Video D... | Provide a detailed description of the following dataset: MetaVD |
ProSLU | In the paper, to bridge the research gap, we propose a new and important task, Profile-based Spoken Language Understanding (ProSLU), which requires a model not only depends on the text but also on the given supporting profile information.
We further introduce a Chinese human-annotated dataset, with over 5K utterances a... | Provide a detailed description of the following dataset: ProSLU |
SERV-CT | Endoscopic stereo reconstruction for surgical scenes gives rise to specific problems, including the lack of clear corner features, highly specular surface properties, and the presence of blood and smoke. These issues present difficulties for both stereo reconstruction itself and also for standardised dataset production... | Provide a detailed description of the following dataset: SERV-CT |
ASL-Skeleton3D | The ASL-Skeleton3D introduces a representation based on mapping into the three-dimensional space the coordinates of the signers in the ASLLVD dataset. This enables a more accurate observation of the body parts and the signs articulation, allowing researchers to better understand the language and explore other approache... | Provide a detailed description of the following dataset: ASL-Skeleton3D |
ASL-Phono | The ASL-Phono introduces a novel linguistics-based representation, which describes the signs in the ASLLVD dataset in terms of a set of attributes of the American Sign Language phonology. | Provide a detailed description of the following dataset: ASL-Phono |
ASLLVD | Extremely important: The ASLLVD video data are subject to Terms of Use:
http://www.bu.edu/asllrp/signbank-terms.pdf.
By downloading these video files, you are agreeing to respect these conditions. In particular,
NO FURTHER REDISTRIBUTION OF THESE VIDEO FILES is allowed.
----------
The American Sign Language... | Provide a detailed description of the following dataset: ASLLVD |
MRSpineSeg Challenge | 1、 Competition name:
The 2nd China Society of Image and Graphics (CSIG) Image and Graphics Technology Challenge: MRSpineSeg Challenge: Automated Multi-class Segmentation of Spinal Structures on Volumetric MR Images.
2、 Purpose：
Degenerative spine diseases (e.g., lumbar disc herniation, spinal stenosis, etc.) h... | Provide a detailed description of the following dataset: MRSpineSeg Challenge |
DIDI Dataset | The dataset contains digital ink drawings of diagrams with dynamic drawing information. The dataset aims to foster research in interactive graphical symbolic understanding. The dataset was obtained using a prompted data collection effort. | Provide a detailed description of the following dataset: DIDI Dataset |
OULU-NPU | The Oulu-NPU face presentation attack detection database consists of 4950 real access and attack videos. These videos were recorded using the front cameras of six mobile devices (Samsung Galaxy S6 edge, HTC Desire EYE, MEIZU X5, ASUS Zenfone Selfie, Sony XPERIA C5 Ultra Dual and OPPO N3) in three sessions with differen... | Provide a detailed description of the following dataset: OULU-NPU |
Wiki-One | This dataset is a Wikipedia dump, split by relations to perform Few-Shot Knowledge Graph Completion.
\begin{table}[]
\begin{tabular}{@{}lllccl@{}}
\textbf{Dataset} & \textbf{\# Ent} & \textbf{\# Rel} & \textbf{\# Triplets} & \textbf{Train/Dev/Test} \\
Wiki-One & 4,838,244 & 822... | Provide a detailed description of the following dataset: Wiki-One |
FACTIFY | FACTIFY is a dataset on multi-modal fact verification. It contains images, textual claim, reference textual documenta and image. The task is to classify the claims into support, not-enough-evidence and refute categories with the help of the supporting data. We aim to combat fake news in the social media era by providin... | Provide a detailed description of the following dataset: FACTIFY |
DurLAR | DurLAR is a high-fidelity 128-channel 3D LiDAR dataset with panoramic ambient (near infrared) and reflectivity imagery for multi-modal autonomous driving applications. Compared to existing autonomous driving task datasets, DurLAR has the following novel features:
- High vertical resolution **LiDAR** with **128 ch... | Provide a detailed description of the following dataset: DurLAR |
BLP | A blackout poetry dataset constructed from publicly available short stories and large poems. The dataset consists of two variants: 8K and 16K examples of passages along with a poem generated from the passage and the indices of the words in the passage from which words in the poem have been selected. The dataset also co... | Provide a detailed description of the following dataset: BLP |
NICO | I.I.D. hypothesis between training and testing data is the basis of numerous image classification methods. Such property can hardly be guaranteed in practice where the Non-IIDness is common, causing in- stable performances of these models. In literature, however, the Non-I.I.D. image classification problem is largely u... | Provide a detailed description of the following dataset: NICO |
Atari 100k | Atari Games for only 100k environment steps. (400k frames with frame-skip=4). | Provide a detailed description of the following dataset: Atari 100k |
GOTOV | Stylianos ParaschiakosStylianos Paraschiakos, Beekman M. (Marian), Knobbe A. (Arno), Cachucho R. (Ricardo), Slagboom P. (Eline)
Wearable sensor-based data of physical activities and indirect calorimetry for 35 (14 female, 21 male) healthy older individuals (over 60 years old). The data has been collected from differen... | Provide a detailed description of the following dataset: GOTOV |
SaL-Lightning | **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 researcher... | Provide a detailed description of the following dataset: SaL-Lightning |
Weibo21 | **Weibo21** is a benchmark of fake news dataset for multi-domain fake news detection (MFND) with domain label annotated, which consists of 4,488 fake news and 4,640 real news from 9 different domains. | Provide a detailed description of the following dataset: Weibo21 |
H2O | The **Human-to-Human-or-Object Interaction Dataset** (**H2O**) dataset is a dataset for Human-Object Interaction (HOI) detection. It consists in determining and locating the list of triplets <subject,verb,target> which describe all the simultaneous interactions in an image.
H²O is composed of the 10 301 images from ... | Provide a detailed description of the following dataset: H2O |
ERD | **ERD** (Educational Resource Discovery) is a corpus of 39,728 manually labeled web resources and 659 queries from NLP, Computer Vision (CV), and Statistics (STATS) for educational resource discovery. | Provide a detailed description of the following dataset: ERD |
LoRa RF | This is a large-scale RF fingerprinting dataset, collected from 25 different LoRa-enabled IoT transmitting devices using USRP B210 receivers. Our dataset consists of a large number of SigMF-compliant binary files representing the I/Q time-domain samples and their corresponding FFT-based files of LoRa transmissions. | Provide a detailed description of the following dataset: LoRa RF |
Turath-150K | **Turath-150K** is a database of images of the Arab world that reflect objects, activities, and scenarios commonly found there.
Broadly, the database consists of objects, activities, and scenarios commonly encountered in the Arab World (from Mauritania in the West of Africa to Iraq). More specifically, there exist 3... | Provide a detailed description of the following dataset: Turath-150K |
FS2K | **FS2K** is a high-quality Facial Sketch Synthesis (FSS). It consists of 2,104 image-sketch pairs spanning three types of sketch styles, image backgrounds, lighting conditions, skin colors, and facial attributes. FS2K differs from previous FSS datasets in difficulty, diversity, and scalability, and should thus facilita... | Provide a detailed description of the following dataset: FS2K |
KIND | 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 disco... | Provide a detailed description of the following dataset: KIND |
SFU-HW-Tracks | **SFU-HW-Tracks** is a dataset for Object Tracking on raw video sequences that contains object annotations with unique object identities (IDs) for the High Efficiency Video Coding (HEVC) v1 Common Test Conditions (CTC) sequences. Ground-truth annotations for 13 sequences were prepared and released as the dataset called... | Provide a detailed description of the following dataset: SFU-HW-Tracks |
YACLC | **YACLC** is a large scale, multidimensional annotated Chinese learner corpus. To construct the corpus, the aurhots first obtain a large number of topic-rich texts generated by Chinese as Foreign Language (CFL) learners. The authors collected and annotated 32,124 sentences written by CFL learners from the lang-8 platfo... | Provide a detailed description of the following dataset: YACLC |
The Benchmark | **The Benchmark** is a collection of datasets for Monocular Height Estimation. It consists of two datasets: GTAH and AHN.
**GTAH** (Grand Theft Auto for Height estimation) is a large-scale synthetic dataset which is obtained from the game Grand Theft Auto, under different imaging conditions. GTAH contains 28,627 hei... | Provide a detailed description of the following dataset: The Benchmark |
CUGE | **CUGE** is a Chinese Language Understanding and Generation Evaluation benchmark with the following features: (1) Hierarchical benchmark framework, where datasets are principally selected and organized with a language capability-task-dataset hierarchy. (2) Multi-level scoring strategy, where different levels of model p... | Provide a detailed description of the following dataset: CUGE |
N-Omniglot | **N-Omniglot** is a neuromorphic dataset for few-shot learning. It contains 1,623 categories of handwritten characters, with only 20 samples per class. | Provide a detailed description of the following dataset: N-Omniglot |
nvBench | **nvBench** is a large-scale NL2VIS (natural languagge to visualisations) benchmark, containing 25,750 (NL, VIS) pairs from 750 tables over 105 domains, synthesized from (NL, SQL) benchmarks to support cross-domain NLPVIS (Natural Language Query to Visualization) task. | Provide a detailed description of the following dataset: nvBench |
BPOD | **Brown Pedestrian Odometry Dataset** (**BPOD**) is a dataset for benchmarking visual odometry algorithms in head-mounted pedestrian settings. This dataset was captured using synchronized global and rolling shutter stereo cameras in 12 diverse indoor and outdoor locations on Brown University's campus. Compared to exist... | Provide a detailed description of the following dataset: BPOD |
HSPACE | **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, an... | Provide a detailed description of the following dataset: HSPACE |
PandaSet | **PandaSet** is a dataset produced by a complete, high-precision autonomous vehicle sensor kit with a no-cost commercial license. The dataset was collected using one 360x360 mechanical spinning LiDAR, one forward-facing, long-range LiDRAR, and 6 cameras. The datasets contains more than 100 scenes, each of which is 8 se... | Provide a detailed description of the following dataset: PandaSet |
EgoBody | **EgoBody** dataset is a novel large-scale dataset for egocentric 3D human pose, shape and motions under interactions in complex 3D scenes. | Provide a detailed description of the following dataset: EgoBody |
RLD | **RLD** (Responsive Listener Dataset) is a conversation video corpus collected from the public resources featuring 67 speakers, 76 listeners with three different attitudes. Through non-verbal signals response to the speakers' words, intonations, or behaviors in real-time, listeners show how they are engaged in dialogue... | Provide a detailed description of the following dataset: RLD |
EMDS-6 | In EMDS-6, there are 21 classes of environmental microorganisms (EMs). In each calss, there are 40 EM original images and their corresponding binary groud truth images. In ground truth images, the foreground is white and background is black. | Provide a detailed description of the following dataset: EMDS-6 |
Industrial Benchmark Dataset for Customer Escalation Prediction | This is a real-world industrial benchmark dataset from a major medical device manufacturer for the prediction of customer escalations. The dataset contains features derived from IoT (machine log) and enterprise data including labels for escalation from a fleet of thousands of customers of high-end medical devices.
... | Provide a detailed description of the following dataset: Industrial Benchmark Dataset for Customer Escalation Prediction |
CeyMo | CeyMo is a novel benchmark dataset for road marking detection which covers a wide variety of challenging urban, sub-urban and rural road scenarios. The dataset consists of 2887 total images of 1920 × 1080 resolution with 4706 road marking instances belonging to 11 classes. The test set is divided into six categories: n... | Provide a detailed description of the following dataset: CeyMo |
DSIFN-CD | The dataset is manually collected from Google Earth. It consists of six large bi-temporal high resolution images covering six cities (i.e., Beijing, Chengdu, Shenzhen, Chongqing, Wuhan, Xian) in China. The five large image-pairs (i.e., Beijing, Chengdu, Shenzhen, Chongqing, Wuhan) are clipped into 394 subimage pairs wi... | Provide a detailed description of the following dataset: DSIFN-CD |
SCROLLS | ** SCROLLS** (Standardized CompaRison Over Long Language Sequences) is an NLP benchmark consisting of a suite of tasks that require **reasoning over long texts**. SCROLLS contains summarization, question answering, and natural language inference tasks, covering multiple domains, including literature, science, business,... | Provide a detailed description of the following dataset: SCROLLS |
CrossMoDA | ****CrossMoDA** is a large and multi-class benchmark for unsupervised cross-modality Domain Adaptation. The goal of the challenge is to segment two key brain structures involved in the follow-up and treatment planning of vestibular schwannoma (VS): the VS and the cochleas. Currently, the diagnosis and surveillance in p... | Provide a detailed description of the following dataset: CrossMoDA |
DADA-seg | DADA-seg is a pixel-wise annotated accident dataset, which contains a variety of critical scenarios from traffic accidents. It is used for semantic segmentation. | Provide a detailed description of the following dataset: DADA-seg |
MyoPS | **MyoPS** is a dataset for myocardial pathology segmentation combining three-sequence cardiac magnetic resonance (CMR) images, which was first proposed in the MyoPS challenge, in conjunction with MICCAI 2020. The challenge provided 45 paired and pre-aligned CMR images, allowing algorithms to combine the complementary i... | Provide a detailed description of the following dataset: MyoPS |
3D-BSLS-6D | Dataset consist of both real captures from Photoneo PhoXi structured light scanner devices annotated by hand and synthetic samples produced by custom generator. In comparison with existing datasets for 6D pose estimation, some notable differences include:
* most of the captured bins are texture-less, made from unifo... | Provide a detailed description of the following dataset: 3D-BSLS-6D |
FR-FS | The FR-FS dataset contains 417 videos collected from FIV dataset and Pingchang 2018 Winter Olympic Games. FR-FS contains the critical movements of the athlete’s take-off, rotation, and landing. Among them, 276 are smooth landing videos, and 141 are fall videos.
To test the generalization performance of our proposed mo... | Provide a detailed description of the following dataset: FR-FS |
results-A | The results-A dataset is a dataset consisting of 22 infrared images commonly used for testing performance of Infrared Image Super-Resolution models. | Provide a detailed description of the following dataset: results-A |
results-C | The results-C dataset is a dataset consisting of 22 infrared images commonly used for testing performance of Infrared Image Super-Resolution models. | Provide a detailed description of the following dataset: results-C |
GrailQA | GrailQA is a new large-scale, high-quality dataset for question answering on knowledge bases (KBQA) on Freebase with 64,331 questions annotated with both answers and corresponding logical forms in different syntax (i.e., SPARQL, S-expression, etc.). It can be used to test three levels of generalization in KBQA: i.i.d.,... | Provide a detailed description of the following dataset: GrailQA |
EurekaAlert | This dataset contains around 5000 scholarly articles and their corresponding easy summary from eureka alert blog, the dataset can be used for the combined task of summarization and simplification. | Provide a detailed description of the following dataset: EurekaAlert |
UAV-VeID | 1. Data Collection
We simulate real scenarios as much as possible during the UAV videos collection.
Specifically, UAV videos are collected from different locations with distinct backgrounds and lighting conditions, e.g., including highways, urban road intersections, parking lots, etc.
For vehicles at parking lots,... | Provide a detailed description of the following dataset: UAV-VeID |
ITB | **Informative Tracking Benchmark** (**ITB**) is a small and informative tracking benchmark with 7% out of 1.2 M frames of existing and newly collected datasets, which enables efficient evaluation while ensuring effectiveness. Specifically, the authors designed a quality assessment mechanism to select the most informati... | Provide a detailed description of the following dataset: ITB |
PhysNLU | **PhysNLU** is a collection of 4 core datasets related to sentence classification, ordering, and coherence of physics explanations based on related tasks. Each dataset comprises explanations extracted from Wikipedia including derivations and mathematical language. | Provide a detailed description of the following dataset: PhysNLU |
Incidents1M | **Incidents1M** is a large-scale multi-label dataset for incident detection which contains 977,088 images, with 43 incident and 49 place categories. It is an evolution of the [Incidents](/dataset/incidents) dataset that doubles the dataset size and includes more incident labels. | Provide a detailed description of the following dataset: Incidents1M |
CVSS | **CVSS** is a massively multilingual-to-English speech to speech translation (S2ST) corpus, covering sentence-level parallel S2ST pairs from 21 languages into English. CVSS is derived from the [Common Voice](common-voice) speech corpus and the [CoVoST](covost) 2 speech-to-text translation (ST) corpus, by synthesizing ... | Provide a detailed description of the following dataset: CVSS |
PerCQA | PerCQA is the first Persian dataset for CQA (Community Question Answering). This dataset contains the questions and answers crawled from the most well-known Persian forum. | Provide a detailed description of the following dataset: PerCQA |
ArtImage | **ArtImage** is a synthetic dataset of articulated object models of 5 categories from PartNet-Mobility for articulated object tasks in category level. | Provide a detailed description of the following dataset: ArtImage |
ASCEND | **ASCEND** (A Spontaneous Chinese-English Dataset) introduces a high-quality resource of spontaneous multi-turn conversational dialogue Chinese code-switching corpus collected in Hong Kong. ASCEND includes 23 bilinguals that are fluent in both Chinese and English and consists of 10.62 hours clean speech corpus. | Provide a detailed description of the following dataset: ASCEND |
MetaEval | **MetaEval** is a collection of 101 NLP tasks. It consists of 101 tasks in a benchmark that can be used for future probing and transfer learning. | Provide a detailed description of the following dataset: MetaEval |
Learn2Reg | **Learn2Reg** is a dataset for medical image registration. Learn2Reg covers a wide range of anatomies (brain, abdomen, and thorax), modalities (ultrasound, CT, MR), availability of annotations, as well as intra- and inter-patient registration evaluation. | Provide a detailed description of the following dataset: Learn2Reg |
LOOK | **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 | Provide a detailed description of the following dataset: LOOK |
VocBench | **VocBench** is a framework that benchmark the performance of state-of-the art neural vocoders. VocBench uses a systematic study to evaluate different neural vocoders in a shared environment that enables a fair comparison between them. | Provide a detailed description of the following dataset: VocBench |
ES-ImageNet | **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 | Provide a detailed description of the following dataset: ES-ImageNet |
CD&S | The Corn Disease and Severity (**CD&S**) dataset consists of 511, 524, and 562, field acquired raw images, corresponding to three common foliar corn diseases, namely Northern Leaf Blight (NLB), Gray Leaf Spot (GLS), and Northern Leaf Spot. | Provide a detailed description of the following dataset: CD&S |
NOD | 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... | Provide a detailed description of the following dataset: NOD |
Curlie | **Curlie dataset** is a dataset with more than 1M websites in 92 languages with relative labels collected from Curlie, the largest multilingual crowdsourced Web directory. The dataset contains 14 website categories aligned across languages. It is used for language-agnostic website embedding and classification | Provide a detailed description of the following dataset: Curlie |
BNATURE | This is a dataset for Bengali Captioning from Images. | Provide a detailed description of the following dataset: BNATURE |
DeepLesion | The National Institutes of Health’s Clinical Center has made a large-scale dataset of CT images publicly available to help the scientific community improve detection accuracy of lesions. While most publicly available medical image datasets have less than a thousand lesions, this dataset, named DeepLesion, has over 32,0... | Provide a detailed description of the following dataset: DeepLesion |
BRACS | BReAst Carcinoma Subtyping (**BRACS**) dataset, a large cohort of annotated Hematoxylin & Eosin (H&E)-stained images to facilitate the characterization of breast lesions. BRACS contains 547 Whole-Slide Images (WSIs), and 4539 Regions of Interest (ROIs) extracted from the WSIs. Each WSI, and respective ROIs, are annotat... | Provide a detailed description of the following dataset: BRACS |
EEGEyeNet | **EEEyeNet** is a dataset and benchmark with the goal of advancing research in the intersection of brain activities and eye movements. It consists of simultaneous Electroencephalography (EEG) and Eye-tracking (ET) recordings from 356 different subjects collected from three different experimental paradigms. | Provide a detailed description of the following dataset: EEGEyeNet |
PaSa | **PaSa** is a dataset to train Machine Learning algorithms to automate the highlighting of patent paragraphs with semantic annotations. It consists of 150k samples obtained by traversing USPTO patents over a decade | Provide a detailed description of the following dataset: PaSa |
CUB-GHA | **CUB-GHA** is a dataset for fine-grained classification with human attention annotations. The dataset collects human gaze data for the fine-grained classification dataset CUB and builds a dataset named CUB-GHA (Gaze-based Human Attention). | Provide a detailed description of the following dataset: CUB-GHA |
UMLS | Source: [Convolutional 2D Knowledge Graph Embeddings](https://arxiv.org/abs/1707.01476) | Provide a detailed description of the following dataset: UMLS |
FFHQ-Text | **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)](https://github.com/NVlabs/ffhq-da... | Provide a detailed description of the following dataset: FFHQ-Text |
Semantic Question Similarity in Arabic | [NSURL-2019 Shared Task 8: Semantic Question Similarity in Arabic](https://aclanthology.org/2019.nsurl-1.1.pdf)
This dataset contains 11,997 pairs of questions in MSA Arabic that are assigned either a label of 0, for no semantic similarity, or 1 otherwise. | Provide a detailed description of the following dataset: Semantic Question Similarity in Arabic |
Sepehr_RumTel01 | The expansion of social networks has accelerated the transmission of information and news at every communities. Over the past few years, the number of users, audiences and social networking publishers, are increased dramatically too. Among the massive amounts of information and news reported on these networks, we are f... | Provide a detailed description of the following dataset: Sepehr_RumTel01 |
BanglaEmotion | **BanglaEmotion** is a manually annotated Bangla Emotion corpus, which incorporates the diversity of fine-grained emotion expressions in social-media text. More fine-grained emotion labels are considered such as Sadness, Happiness, Disgust, Surprise, Fear and Anger - which are, according to Paul Ekman (1999), the six b... | Provide a detailed description of the following dataset: BanglaEmotion |
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