dataset_name stringlengths 2 128 | description stringlengths 1 9.7k | prompt stringlengths 59 185 |
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CalMS21 | The Caltech Mouse Social Interactions (CalMS21) dataset is a multi-agent dataset from behavioral neuroscience. The dataset consists of trajectory data of social interactions, recorded from videos of freely behaving mice in a standard resident-intruder assay. The CalMS21 dataset is part of the Multi-Agent Behavior Chall... | Provide a detailed description of the following dataset: CalMS21 |
HumAID | Social networks are widely used for information consumption and dissemination, especially during time-critical events such as natural disasters. Despite its significantly large volume, social media content is often too noisy for direct use in any application. Therefore, it is important to filter, categorize, and concis... | Provide a detailed description of the following dataset: HumAID |
PlasticineLab | PasticineLab is a differentiable physics benchmark, which includes a diverse collection of soft body manipulation tasks. In each task, the agent uses manipulators to deform the plasticine into the desired configuration. The underlying physics engine supports differentiable elastic and plastic deformation using the Diff... | Provide a detailed description of the following dataset: PlasticineLab |
DFUC2021 | The Diabetic Foot Ulcers dataset (DFUC2021) is a dataset for analysis of pathology, focusing on infection and ischaemia. The final release of DFUC2021 consists of 15,683 DFU patches, with 5,955 training, 5,734 for testing and 3,994 unlabeled DFU patches. The ground truth labels are four classes, i.e. control, infection... | Provide a detailed description of the following dataset: DFUC2021 |
UAV-Human | UAV-Human is a large dataset for human behavior understanding with UAVs. It contains 67,428 multi-modal video sequences and 119 subjects for action recognition, 22,476 frames for pose estimation, 41,290 frames and 1,144 identities for person re-identification, and 22,263 frames for attribute recognition. The dataset wa... | Provide a detailed description of the following dataset: UAV-Human |
Criteo Attribution Modeling Dataset | Content of this dataset
This dataset includes following files:
README.md
criteo_attribution_dataset.tsv.gz: the dataset itself (623M compressed)
Experiments.ipynb: ipython notebook with code and utilities to reproduce the results in the paper. Can also be used as a starting point for further research on this data... | Provide a detailed description of the following dataset: Criteo Attribution Modeling Dataset |
BSTC | BSTC (Baidu Speech Translation Corpus) is a large-scale dataset for automatic simultaneous interpretation. BSTC version 1.0 contains 50 hours of real speeches, including three parts, the audio files, the transcripts, and the translations. The corpus can be used to build automatic simultaneous interpretation system.
Th... | Provide a detailed description of the following dataset: BSTC |
READ 2016 | This dataset arises from the READ project (Horizon 2020).
The dataset consists of a subset of documents from the Ratsprotokolle collection composed of minutes of the council meetings held from 1470 to 1805 (about 30.000 pages), which will be used in the READ project. This dataset is written in Early Modern German. T... | Provide a detailed description of the following dataset: READ 2016 |
RIMES | The RIMES database (Reconnaissance et Indexation de données Manuscrites et de fac similÉS / Recognition and Indexing of handwritten documents and faxes) was created to evaluate automatic systems of recognition and indexing of handwritten letters. Of particular interest are cases such as those sent by postal mail or fax... | Provide a detailed description of the following dataset: RIMES |
Twitter-MEL | Twitter-MEL is a multimodal entity linking (MEL) dataset built from Twitter. The dataset consists of tweets that had both text and images, with a total of 2.6M timeline tweets and 20k entities. | Provide a detailed description of the following dataset: Twitter-MEL |
PhoNER COVID19 | PhoNER_COVID19 is a dataset for recognising COVID-19 related named entities in Vietnamese, consisting of 35K entities over 10K sentences. The authors defined 10 entity types with the aim of extracting key information related to COVID-19 patients, which are especially useful in downstream applications. In general, these... | Provide a detailed description of the following dataset: PhoNER COVID19 |
CAMUS | This project aims to provide all the materials to the community to resolve the problem of echocardiographic image segmentation and volume estimation from 2D ultrasound sequences (both two and four-chamber views). To this aim, the following solutions were set up.
1. Introduction of the largest publicly-available and ... | Provide a detailed description of the following dataset: CAMUS |
ORBIT | ORBIT is a real-world few-shot dataset and benchmark grounded in a real-world application of teachable object recognizers for people who are blind/low vision. The dataset contains 3,822 videos of 486 objects recorded by people who are blind/low-vision on their mobile phones, and the benchmark reflects a realistic, high... | Provide a detailed description of the following dataset: ORBIT |
DexYCB | DexYCB is a dataset for capturing hand grasping of objects. It can be used three relevant tasks: 2D object and keypoint detection, 6D object pose estimation, and 3D hand pose estimation.
The dataset was built using 20 objects from the YCB-Video dataset, and consists of multiple trials from 10 subjects. For each tri... | Provide a detailed description of the following dataset: DexYCB |
FM2 | FoolMeTwice (FM2 for short) is a large dataset of challenging entailment pairs collected through a fun multi-player game. Gamification encourages adversarial examples, drastically lowering the number of examples that can be solved using "shortcuts" compared to other popular entailment datasets. Players are presented wi... | Provide a detailed description of the following dataset: FM2 |
ManyTypes4Py | ManyTypes4Py is a large Python dataset for machine learning (ML)-based type inference. The dataset contains a total of 5,382 Python projects with more than 869K type annotations. Duplicate source code files were removed to eliminate the negative effect of the duplication bias. To facilitate training and evaluation of M... | Provide a detailed description of the following dataset: ManyTypes4Py |
EtymDB 2.0 | A multilingual etymological database extracted from the Wiktionary (described in Methodological Aspects of Developing and Managing an Etymological Lexical Resource: Introducing EtymDB-2.0) | Provide a detailed description of the following dataset: EtymDB 2.0 |
ContraCAT | Current approaches to context-aware MT rely on a set of surface heuristics to translate pronouns, which break down when translations require real reasoning. We create a new template test set ContraCAT to assess the ability of Machine Translation to handle the specific steps necessary for successful pronoun translation... | Provide a detailed description of the following dataset: ContraCAT |
SynD | SynD is a synthetic energy dataset with a focus on residential buildings. This dataset is the result of a custom simulation process that relies on power traces of household appliances. The output of simulations is the power consumption of 21 household appliances as well as the household-wide consumption (i.e. mains). T... | Provide a detailed description of the following dataset: SynD |
Samanantar | Samanantar is the largest publicly available parallel corpora collection for Indic languages: Assamese, Bengali, Gujarati, Hindi, Kannada, Malayalam, Marathi, Oriya, Punjabi, Tamil, Telugu. The corpus has 49.6M sentence pairs between English to Indian Languages. | Provide a detailed description of the following dataset: Samanantar |
MindReader | MindReader is a novel dataset providing explicit user ratings over a knowledge graph within the movie domain. The latest stable version of the dataset contains 218,794 ratings from 2,316 users over 12,206 entities entities, and an associated knowledge graph consisting of 18,133 movie-related entities. The dataset is co... | Provide a detailed description of the following dataset: MindReader |
WEC-Eng | WEC-eng is a cross-document event coreference resolution dataset extracted from English Wikipedia. Coreference links are not restricted within predefined topics. The training set includes 40,529 mentions distributed into 7,042 coreference clusters. | Provide a detailed description of the following dataset: WEC-Eng |
FreSaDa | FreSaDa is a French satire dataset for cross-domain satire detection, which is composed of 11,570 articles from the news domain. The dataset samples have been split into training, validation and test, such that the training publication sources are distinct from the validation and test publication sources. This gives ri... | Provide a detailed description of the following dataset: FreSaDa |
L3DAS21 | L3DAS21 is a dataset for 3D audio signal processing. It consists of a 65 hours 3D audio corpus, accompanied with a Python API that facilitates the data usage and results submission stage.
The LEDAS21 datasets contain multiple-source and multiple-perspective B-format Ambisonics audio recordings. The authors sampled ... | Provide a detailed description of the following dataset: L3DAS21 |
SI-Score | **SI-SCORE** is a synthetic dataset for the analysis of robustness to object location, rotation and size. It consists of images that vary only for factors like object size and object location.
SI-SCORE was built by taking objects and backgrounds and systematically varying object size, location and rotation angle so ... | Provide a detailed description of the following dataset: SI-Score |
RLU | RL Unplugged is suite of benchmarks for offline reinforcement learning. The RL Unplugged is designed around the following considerations: to facilitate ease of use, we provide the datasets with a unified API which makes it easy for the practitioner to work with all data in the suite once a general pipeline has been est... | Provide a detailed description of the following dataset: RLU |
Multifog KITTI dataset | we propose the augmented KITTI dataset with fog for both camera and LiDAR sensors with different visibility ranges from 20 to 80 meters to best match realistic fog environment. | Provide a detailed description of the following dataset: Multifog KITTI dataset |
OSIC Pulmonary Fibrosis Progression | Imagine one day, your breathing became consistently labored and shallow. Months later you were finally diagnosed with pulmonary fibrosis, a disorder with no known cause and no known cure, created by scarring of the lungs. If that happened to you, you would want to know your prognosis. That’s where a troubling disease b... | Provide a detailed description of the following dataset: OSIC Pulmonary Fibrosis Progression |
QMSum | **QMSum** is a new human-annotated benchmark for query-based multi-domain meeting summarisation task, which consists of 1,808 query-summary pairs over 232 meetings in multiple domains. | Provide a detailed description of the following dataset: QMSum |
SVAMP | A challenge set for elementary-level Math Word Problems (MWP). An MWP consists of a short Natural Language narrative that describes a state of the world and poses a question about some unknown quantities.
The examples in **SVAMP** test a model across different aspects of solving MWPs: 1) Is the model question sensit... | Provide a detailed description of the following dataset: SVAMP |
SPARTQA | **SpartQA** is a textual question answering benchmark for spatial reasoning on natural language text which contains more realistic spatial phenomena not covered by prior datasets and that is challenging for state-of-the-art language models (LM).
SPARTQA is built on NLVR’s images containing more objects with richer s... | Provide a detailed description of the following dataset: SPARTQA |
StylePTB | **StylePTB** is a fine-grained text style transfer benchmark. It consists of paired sentences undergoing 21 fine-grained stylistic changes spanning atomic lexical, syntactic, semantic, and thematic transfers of text, as well as compositions of multiple transfers which allow modelling of fine-grained stylistic changes a... | Provide a detailed description of the following dataset: StylePTB |
NorDial | **NorDial** is the first step to creating a corpus of dialectal variation of written Norwegian. It consists of small corpus of tweets manually annotated as Bokmål, Nynorsk, any dialect, or a mix. | Provide a detailed description of the following dataset: NorDial |
FixMyPose | **FixMyPose** is a dataset for automated pose correction. It consists of descriptions to correct a "current" pose to look like a "target" pose, in English and Hindi. The collected descriptions have interesting linguistic properties such as egocentric relations to environment objects, analogous references, etc., requiri... | Provide a detailed description of the following dataset: FixMyPose |
AcinoSet | **AcinoSet** is a dataset of free-running cheetahs in the wild that contains 119,490 frames of multi-view synchronized high-speed video footage, camera calibration files and 7,588 human-annotated frames. The authors utilized markerless animal pose estimation with DeepLabCut to provide 2D keypoints (in the 119K frames).... | Provide a detailed description of the following dataset: AcinoSet |
Vietnamese intent detection and slot filling | This is a dataset for intent detection and slot filling for the Vietnamese language. The dataset consists of 5,871 gold annotated utterances with 28 intent labels and 82 slot types. | Provide a detailed description of the following dataset: Vietnamese intent detection and slot filling |
XFORMAL | ** XFORMAL** is a multilingual formal style transfer benchmark of multiple formal reformulations of informal text in Brazilian Portuguese, French, and Italian. | Provide a detailed description of the following dataset: XFORMAL |
SSN | **SSN** (short for Semantic Scholar Network) is a scientific papers summarization dataset which contains 141K research papers in different domains and 661K citation relationships. The entire dataset constitutes a large connected citation graph. | Provide a detailed description of the following dataset: SSN |
Global Wheat | Global WHEAT Dataset is the first large-scale dataset for wheat head detection from field optical images. It included a very large range of cultivars from differents continents. Wheat is a staple crop grown all over the world and consequently interest in wheat phenotyping spans the globe. Therefore, it is important tha... | Provide a detailed description of the following dataset: Global Wheat |
Brain-Score | The Brain-Score platform aims to yield strong computational models of the ventral stream. We enable researchers to quickly get a sense of how their model scores against standardized brain benchmarks on multiple dimensions and facilitate comparisons to other state-of-the-art models. At the same time, new brain data can ... | Provide a detailed description of the following dataset: Brain-Score |
ACDC Scribbles | We release expert-made scribble annotations for the medical ACDC dataset [1]. The released data must be considered as extending the original ACDC dataset.
The ACDC dataset contains cardiac MRI images, paired with hand-made segmentation masks. It is possible to use the segmentation masks provided in the ACDC dataset to... | Provide a detailed description of the following dataset: ACDC Scribbles |
Synthetic COVID-19 CXR Dataset | A public open dataset of synthetic chest X-ray images of COVID-19.
The dataset consists of 21,295 synthetic COVID-19 chest X-ray images. Images are generated using an unsupervised domain adaptation approach by leveraging class conditioning and adversarial training from source datasets [RSNA Kaggle Dataset](https://a... | Provide a detailed description of the following dataset: Synthetic COVID-19 CXR Dataset |
Twitter Stance Election 2020 | The data set contains 2500 manually-stance-labeled tweets, 1250 for each candidate (Joe Biden and Donald Trump). These tweets were sampled from the unlabeled set that our research team collected English tweets related to the 2020 US Presidential election. Through the Twitter Streaming API, the authors collected data us... | Provide a detailed description of the following dataset: Twitter Stance Election 2020 |
A2D Sentences | The Actor-Action Dataset (A2D) by Xu et al. [29] serves as the largest video dataset for the general actor and action segmentation task. It contains 3,782 videos from YouTube with pixel-level labeled actors and their actions. The dataset includes eight different actions, while a total of seven actor classes are conside... | Provide a detailed description of the following dataset: A2D Sentences |
NewsCLIPpings | **NewsCLIPpings** is a dataset for detecting mismatched images and captions. Different to previous misinformation datasets, in NewsCLIPpings both the images and captions are unmanipulated, but some of them are mismatched. | Provide a detailed description of the following dataset: NewsCLIPpings |
Countix-AV | **Countix-AV** is a dataset for repetitive action counting by sight and sound created by repurposing the [Countix](countix) dataset.
It is created by selecting 19 categories from Countix for which the repetitive action has a clear sound, such as clapping, playing tennis, etc. The dataset contains 1,863 videos, with 98... | Provide a detailed description of the following dataset: Countix-AV |
Referring Expressions for DAVIS 2016 & 2017 | Our task is to localize and provide a pixel-level mask of an object on all video frames given a language referring expression obtained either by looking at the first frame only or the full video. To validate our approach we employ two popular video object segmentation datasets, DAVIS16 [38] and DAVIS17 [42]. These two ... | Provide a detailed description of the following dataset: Referring Expressions for DAVIS 2016 & 2017 |
IIIT-ILST | **IIIT-ILST** is a dataset and benchmark for scene text recognition for three Indic scripts - Devanagari, Telugu and Malayalam. IIIT-ILST contains nearly 1000 real images per each script which are annotated for scene text bounding boxes and transcriptions. | Provide a detailed description of the following dataset: IIIT-ILST |
A2Dre | We obtain A2Dre by selecting only instances that were labeled as non-trivial, which are 433 REs from 190 videos. We do not use the trivial cases as the analysis of such examples is not relevant, as referents can be described by using the category alone. Each annotator was presented with a RE, a video in which the targe... | Provide a detailed description of the following dataset: A2Dre |
A2Dre+ | A2Dre is a subset from the A2D test set including $433$~\textit{non-trivial} REs. Due to its highly unbalanced distribution across the $7$~semantic categories we select the $4$~major categories \textsl{appearance, location, motion and static}. The four categories have in common that in most cases, for a given referent,... | Provide a detailed description of the following dataset: A2Dre+ |
RGB-D-D | **RGB-D-D** is a large-scale dataset for depth map super-resolution (SR). It consists of real-world paired low-resolution (LR) and high-resolution (HR) depth maps. The paired LR and HR depth maps are captured from mobile phone and Lucid Helios respectively ranging from indoor scenes to challenging outdoor scenes. | Provide a detailed description of the following dataset: RGB-D-D |
WikiEvents | **WikiEvents** is a document-level event extraction benchmark dataset which includes complete event and coreference annotation. | Provide a detailed description of the following dataset: WikiEvents |
RaindropsOnWindshield | **RaindropsOnWindshield** is a dataset for training and assessing vision algorithms' performance for different tasks of image artifacts detection on either camera lens or windshield. The dataset contains 8190 images, of which 3390 contain raindrops. Images are annotated with the binary mask representing areas with rain... | Provide a detailed description of the following dataset: RaindropsOnWindshield |
How2Sign | The How2Sign is a multimodal and multiview continuous American Sign Language (ASL) dataset consisting of a parallel corpus of more than 80 hours of sign language videos and a set of corresponding modalities including speech, English transcripts, and depth. A three-hour subset was further recorded in the Panoptic studio... | Provide a detailed description of the following dataset: How2Sign |
TNL2K | **Tracking by Natural Language** (**TNL2K**) is constructed for the evaluation of tracking by natural language specification. TNL2K features:
- Large-scale: 2,000 sequences, contains 1,244,340 frames, 663 words, 1300 / 700 for the train / testing respectively
- High-quality: Manual annotation with careful inspec... | Provide a detailed description of the following dataset: TNL2K |
ElBa | ElBa is composed of procedurally-generated realistic renderings, where we vary in a continuous way element
shapes and colors and their distribution, to generate 30K texture images with different local symmetry, stationarity, and density of (3M) localized texels, whose attributes are thus known by construction.
[Dow... | Provide a detailed description of the following dataset: ElBa |
MS^2 | **MS^2** (Multi-Document Summarization of Medical Studies) is a dataset of over 470k documents and 20k summaries derived from the scientific literature. This dataset facilitates the development of systems that can assess and aggregate contradictory evidence across multiple studies, and is one of the first large-scale, ... | Provide a detailed description of the following dataset: MS^2 |
CarFusion | We provide manual annotations of 14 semantic keypoints for 100,000 car instances (sedan, suv, bus, and truck) from 53,000 images captured from 18 moving cameras at Multiple intersections in Pittsburgh, PA. Please fill the google form to get a email with the download links: | Provide a detailed description of the following dataset: CarFusion |
Subjective Discourse | This is a discourse dataset with multiple and subjective interpretations of English conversation in the form of perceived conversation acts and intents. The dataset consists of witness testimonials in U.S. congressional hearings. | Provide a detailed description of the following dataset: Subjective Discourse |
WMT19 Metrics Task | This shared task will examine automatic evaluation metrics for machine translation. The goals of the shared metrics task are:
To achieve the strongest correlation with human judgement of translation quality;
To illustrate the suitability of an automatic evaluation metric as a surrogate for human evaluation;
To add... | Provide a detailed description of the following dataset: WMT19 Metrics Task |
ML-CB | In this paper, we develop a new privacy enhancing tool: ML-CB—a means of using distinguishable pictorial information combined with underlying website source code to produce accurate and robust machine learning classifiers able to discern fingerprinting (i.e., surreptitious tracking) from non-fingerprinting canvas-based... | Provide a detailed description of the following dataset: ML-CB |
Eedi Dataset | The **Eedi dataset** contains from two school years (September 2018 to May 2020) of students’ answers to mathematics questions from Eedi, a leading educational platform which millions of students interact with daily around the globe. Eedi offers diagnostic questions to students from primary to high school (roughly betw... | Provide a detailed description of the following dataset: Eedi Dataset |
KolektorSDD2 | **KolektorSDD2** is a surface-defect detection dataset with over 3000 images containing several types of defects, obtained while addressing a real-world industrial problem.
The dataset consists of:
* 356 images with visible defects
* 2979 images without any defect
* image sizes of approximately 230 x 630 pixels... | Provide a detailed description of the following dataset: KolektorSDD2 |
Quasimodo | Quasimodo is commonsense knowledge base that focuses on salient properties of objects. We provide several subsets:
* Positive statements only
* Positive statements top 10%
* Negated statements only
* Occupations
* Positive statements
* Negative statements
* Animals
* Positive statements
*... | Provide a detailed description of the following dataset: Quasimodo |
HO-3D | A hand-object interaction dataset with 3D pose annotations of hand and object. The dataset contains 66,034 training images and 11,524 test images from a total of 68 sequences. The sequences are captured in multi-camera and single-camera setups and contain 10 different subjects manipulating 10 different objects from YCB... | Provide a detailed description of the following dataset: HO-3D |
DogFaceNet | A dog face dataset for dog face verification and recognition/identification. | Provide a detailed description of the following dataset: DogFaceNet |
Retailrocket | The dataset consists of three files: a file with behaviour data (events.csv), a file with item properties (itemproperties.сsv) and a file, which describes category tree (categorytree.сsv). The data has been collected from a real-world ecommerce website. It is raw data, i.e. without any content transformations, however,... | Provide a detailed description of the following dataset: Retailrocket |
Ulm-TSST | **Ulm-TSST** is a dataset continuous emotion (valence and arousal) prediction and `physiological-emotion' prediction. It consists of a multimodal richly annotated dataset of self-reported, and external dimensional ratings of emotion and mental well-being. After a brief period of preparation the subjects are asked to gi... | Provide a detailed description of the following dataset: Ulm-TSST |
OmniFlow | **OmniFlow** is a synthetic omnidirectional human optical flow dataset. Based on a rendering engine the authors created a naturalistic 3D indoor environment with textured rooms, characters, actions, objects, illumination and motion blur where all components of the environment are shuffled during the data capturing proc... | Provide a detailed description of the following dataset: OmniFlow |
hERG | **hERG** is a large-scale biophysics federated molecular dataset related to cardiac toxicity. It consists of 10,572 compounds, with an average of 29.39 nodes and 94.09 edges in each graph. | Provide a detailed description of the following dataset: hERG |
RTC | **RTC** is a benchmark corpus of social media comments sampled over three years. The corpus consists of 36.36m unlabelled comments for adaptation and evaluation on an upstream masked language modelling task as well as 0.9m labelled comments for finetuning and evaluation on a downstream document classification task.
T... | Provide a detailed description of the following dataset: RTC |
Follicular-Segmentation | The **Follicular-Segmentation** dataset consists of 6900 cropped typical image patches of 1024x1024 pixels containing: follicular areas, colloid areas, and the other blank background areas.
Image source: [https://github.com/bupt-ai-cz/Hybrid-Model-Enabling-Highly-Efficient-Follicular-Segmentation](https://github.com... | Provide a detailed description of the following dataset: Follicular-Segmentation |
Semantic Textual Similarity (2012 - 2016) | Semantic Textual Similarity (2012 - 2016) involves a set of semantic textual similarity datasets that were part of previous shared tasks (2012-2016):
STS12 - [ Semeval-2012 task 6: A pilot on semantic textual similarity](https://www.aclweb.org/anthology/S12-1051/)
STS13 - [SEM 2013 shared task: Semantic Textual S... | Provide a detailed description of the following dataset: Semantic Textual Similarity (2012 - 2016) |
JUSThink Dialogue and Actions Corpus | The information contained in JUSThink Dialogue and Actions Corpus dataset includes dialogue transcripts, event logs, and test responses of children aged 9 through 12, as they participate in a robot-mediated human-human collaborative learning activity named JUSThink, where children in teams of two solve a problem on gra... | Provide a detailed description of the following dataset: JUSThink Dialogue and Actions Corpus |
MediaSpeech | **MediaSpeech** is a media speech dataset (you might have guessed this) built with the purpose of testing Automated Speech Recognition (ASR) systems performance. The dataset consists of short speech segments automatically extracted from media videos available on YouTube and manually transcribed, with some pre- and post... | Provide a detailed description of the following dataset: MediaSpeech |
NISQA Speech Quality Corpus | The NISQA Corpus includes more than 14,000 speech samples with simulated (e.g. codecs, packet-loss, background noise) and live (e.g. mobile phone, Zoom, Skype, WhatsApp) conditions. Each file is labelled with subjective ratings of the overall quality and the quality dimensions Noisiness, Coloration, Discontinuity, and ... | Provide a detailed description of the following dataset: NISQA Speech Quality Corpus |
IBM Debater Mention Detection Benchmark | This dataset contains general and named entities annotations on both clean written text and on noisy speech data.
It includes 1000 sentences from Wikipedia and 1000 sentences of speech data that appear in two forms: (1) transcribed manually, and (2) the output of an ASR engine.
Each of the datasets includes a total... | Provide a detailed description of the following dataset: IBM Debater Mention Detection Benchmark |
HopeEDI | Over the past few years, systems have been developed to control online content and eliminate abusive, offensive or hate speech content. However, people in power sometimes misuse this form of censorship to obstruct the democratic right of freedom of speech. Therefore, it is imperative that research should take a positiv... | Provide a detailed description of the following dataset: HopeEDI |
Apolloscape Trajectory | Our trajectory dataset consists of camera-based images, LiDAR scanned point clouds, and manually annotated trajectories. It is collected under various lighting conditions and traffic densities in Beijing, China. More specifically, it contains highly complicated traffic flows mixed with vehicles, riders, and pedestrians... | Provide a detailed description of the following dataset: Apolloscape Trajectory |
Apolloscape Inpainting | The **Inpainting** dataset consists of synchronized Labeled image and LiDAR scanned point clouds. It's captured by HESAI Pandora All-in-One Sensing Kit. It is collected under various lighting conditions and traffic densities in Beijing, China. | Provide a detailed description of the following dataset: Apolloscape Inpainting |
GooAQ | GooAQ is a large-scale dataset with a variety of answer types. This dataset contains over 5 million questions and 3 million answers collected from Google. GooAQ questions are collected semi-automatically from the Google search engine using its autocomplete feature. This results in naturalistic questions of practical in... | Provide a detailed description of the following dataset: GooAQ |
DiS-ReX | **DiS-ReX** is a multilingual dataset for distantly supervised (DS) relation extraction (RE). The dataset has over 1.5 million instances, spanning 4 languages (English, Spanish, German and French). The dataset has 36 positive relation types + 1 no relation (NA) class. | Provide a detailed description of the following dataset: DiS-ReX |
Concadia | **Concadia** is a publicly available Wikipedia-based corpus, which consists of 96,918 images with corresponding English-language descriptions, captions, and surrounding context. | Provide a detailed description of the following dataset: Concadia |
XLEnt | XLEnt consists of parallel entity mentions in 120 languages aligned with English. These entity pairs were constructed by performing named entity recognition (NER) and typing on English sentences from mined sentence pairs. These extracted English entity labels and types were projected to the non-English sentences throug... | Provide a detailed description of the following dataset: XLEnt |
TREC-COVID | TREC-COVID is a community evaluation designed to build a test collection that captures the information needs of biomedical researchers using the scientific literature during a pandemic. One of the key characteristics of pandemic search is the accelerated rate of change: the topics of interest evolve as the pandemic pro... | Provide a detailed description of the following dataset: TREC-COVID |
NFCorpus | **NFCorpus** is a full-text English retrieval data set for Medical Information Retrieval. It contains a total of 3,244 natural language queries (written in non-technical English, harvested from the NutritionFacts.org site) with 169,756 automatically extracted relevance judgments for 9,964 medical documents (written in ... | Provide a detailed description of the following dataset: NFCorpus |
CQADupStack | CQADupStack is a benchmark dataset for community question-answering research. It contains threads from twelve StackExchange subforums, annotated with duplicate question information. Pre-defined training and test splits are provided, both for retrieval and classification experiments, to ensure maximum comparability betw... | Provide a detailed description of the following dataset: CQADupStack |
SciFact | **SciFact** is a dataset of 1.4K expert-written claims, paired with evidence-containing abstracts annotated with veracity labels and rationales. | Provide a detailed description of the following dataset: SciFact |
Co/FeMn bilayers | Co/FeMn bilayers measured. | Provide a detailed description of the following dataset: Co/FeMn bilayers |
BoostCLIR | **BoostCLIR** is a bilingual (Japanese-English) corpus of patent abstracts, extracted from the MAREC patent data, and the data from the NTCIR PatentMT workshop collections, accompanied with relevance judgements for the task of patent prior-art search.
**Important:** The English side of the corpus contains patent IDs... | Provide a detailed description of the following dataset: BoostCLIR |
ConferenceVideoSegmentationDataset | This is a video and image segmentation dataset for human head and shoulders, relevant for creating elegant media for videoconferencing and virtual reality applications. The source
data includes ten online conference-style green screen videos. The authors extracted 3600 frames from the videos and generated the ground t... | Provide a detailed description of the following dataset: ConferenceVideoSegmentationDataset |
DeCOCO | **DeCOCO** is a bilingual (English-German) corpus of image descriptions, where the English part is extracted from the COCO dataset, and the German part are translations by a native German speaker. | Provide a detailed description of the following dataset: DeCOCO |
HumanMT | **HumanMT** is a collection of human ratings and corrections of machine translations. It consists of two parts: The first part contains five-point and pairwise sentence-level ratings, the second part contains error markings and corrections. Details are described in the following.
I. Sentence-level ratings
This is a... | Provide a detailed description of the following dataset: HumanMT |
MVP | **MVP** is a multi-view partial point cloud dataset (MVP) containing over 100,000 high-quality scans, which renders partial 3D shapes from 26 uniformly distributed camera poses for each 3D CAD model. | Provide a detailed description of the following dataset: MVP |
MetaCLIR | This data adds textual meta-infomation data to two existing corpora for cross language information retrieval: BoostCLIR, and the Large Scale CLIR Dataset (wiki-clir). | Provide a detailed description of the following dataset: MetaCLIR |
WiTA | **WiTA** (Writing in The Air) is a dataset for the challenging writing in the air (WiTA) task -- an elaborate task bridging vision and NLP. The dataset consists of five sub-datasets in two languages (Korean and English) and amounts to 209,926 video instances from 122 participants. Finger movement for WiTA is captured w... | Provide a detailed description of the following dataset: WiTA |
Large-Scale CLIR Dataset | The Large-Scale CLIR Dataset is a retrieval dataset built for Cross-Language Information Retrieval (CLIR).
The dataset is derived from Wikipedia and contains more 2.8 million English single-sentence queries with relevant documents from 25 other selected languages. | Provide a detailed description of the following dataset: Large-Scale CLIR Dataset |
NLmaps | There are two versions of the NLmaps corpus. NLmaps (v1) and its extension NLmaps v2. Both versions of the NLmaps corpus consist of questions about geographical facts that can be answered with the OpenStreetMap (OSM) database (available under the Open Database Licence). The questions are in English and have a correspon... | Provide a detailed description of the following dataset: NLmaps |
SciGen | **SciGen** is a challenge dataset for the task of reasoning-aware data-to-text generation consisting of tables from scientific articles and their corresponding descriptions. The unique properties of SciGen are that (1) tables mostly contain numerical values, and (2) the corresponding descriptions require arithmetic re... | Provide a detailed description of the following dataset: SciGen |
PatTR | **PatTR** is a sentence-parallel corpus extracted from the MAREC patent collection. The current version contains more than 22 million German-English and 18 million French-English parallel sentences collected from all patent text sections as well as 5 million German-French sentence pairs from patent titles, abstracts an... | Provide a detailed description of the following dataset: PatTR |
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