dataset_name stringlengths 2 128 | description stringlengths 1 9.7k | prompt stringlengths 59 185 |
|---|---|---|
DND | Benchmarking Denoising Algorithms with Real Photographs
This dataset consists of 50 pairs of noisy and (nearly) noise-free images captured with four consumer cameras. Since the images are of very high-resolution, the providers extract 20 crops of size 512 × 512 from each image, thus yielding a total of 1000 patches. | Provide a detailed description of the following dataset: DND |
Cityscapes-VPS | Cityscapes-VPS is a video extension of the Cityscapes validation split. It provides 2500-frame panoptic labels that temporally extend the 500 Cityscapes image-panoptic labels. There are total 3000-frame panoptic labels which correspond to 5, 10, 15, 20, 25, and 30th frames of each 500 videos, where all instance ids are... | Provide a detailed description of the following dataset: Cityscapes-VPS |
METU Trademark | The METU Trademark Dataset is a large dataset (the largest publicly available logo dataset as of 2014, and the largest one not requiring any preprocessing as of 2017), which is composed of more than 900K real logos belonging to real companies worldwide. The dataset also includes query sets of varying difficulties, allo... | Provide a detailed description of the following dataset: METU Trademark |
PS-Plant dataset | Automated leaf segmentation is a challenging area in computer vision. Recent advances in machine learning approaches allowed to achieve better results than traditional image processing techniques; however, training such systems often require large annotated data sets. To contribute with annotated data sets and help to ... | Provide a detailed description of the following dataset: PS-Plant dataset |
Real SVBRDF | A total of 80 real material samples were captured in a dark room. For each material, multiple captures were collected at different distances from the camera (between 250 and 650 mm) to observe both macro- and micro-level details. The dataset is mostly comprised of planar specimens but also includes non-planar objects s... | Provide a detailed description of the following dataset: Real SVBRDF |
MLPF | Dataset of 50,000 top quark-antiquark (ttbar) events produced in proton-proton collisions at 14 TeV, overlaid with minimum bias events corresponding to a pileup of 200 on average. The dataset consists of detector hits as the input, generator particles as the ground truth and reconstructed particles from DELPHES for add... | Provide a detailed description of the following dataset: MLPF |
EXPLICIT 3D CHANGE DETECTION USING RAY-TRACING IN SPHERICAL COORDINATES | Real and simulated lidar data of indoor and outdoor scenes, before and after geometric scene changes have occurred. Data include lidar scans from multiple viewpoints with provided coordinate transforms, and manually annotated ground-truth regarding which parts of the scene have changed between subsequent scans. | Provide a detailed description of the following dataset: EXPLICIT 3D CHANGE DETECTION USING RAY-TRACING IN SPHERICAL COORDINATES |
ACFR Orchard Fruit Dataset | ACFR Orchard Fruit Dataset is an agricultural dataset containing images and annotations for different fruits, collected at different farms across Australia. The dataset was gathered by the agriculture team at the Australian Centre for Field Robotics, The University of Sydney, Australia. | Provide a detailed description of the following dataset: ACFR Orchard Fruit Dataset |
University of Washington/Northwestern University (UW/NU) Corpus | The University of Washington/Northwestern University (UW/NU) Corpus contains recordings and textgrids of Pacific Northwest and Northern Cities speakers reading a subset of the IEEE "Harvard" sentences. The UW/NU Corpus Version 1.0 has been used to study the effects of dialectal variation on speech intelligibility, whil... | Provide a detailed description of the following dataset: University of Washington/Northwestern University (UW/NU) Corpus |
UNITOPATHO | Histopathological characterization of colorectal polyps allows to tailor patients' management and follow up with the ultimate aim of avoiding or promptly detecting an invasive carcinoma. Colorectal polyps characterization relies on the histological analysis of tissue samples to determine the polyps malignancy and dyspl... | Provide a detailed description of the following dataset: UNITOPATHO |
WiC-TSV | WiC-TSV is a new multi-domain evaluation benchmark for Word Sense Disambiguation. More specifically, it is a framework for Target Sense Verification of Words in Context which grounds its uniqueness in the formulation as a binary classification task thus being independent of external sense inventories, and the coverage ... | Provide a detailed description of the following dataset: WiC-TSV |
Clinical Admission Notes from MIMIC-III | This dataset is created from **MIMIC-III** ([Medical Information Mart for Intensive Care III](https://paperswithcode.com/dataset/mimic-iii)) and contains simulated patient admission notes. The clinical notes contain information about a patient at **admission time** to the ICU and are labelled for four outcome predictio... | Provide a detailed description of the following dataset: Clinical Admission Notes from MIMIC-III |
IBC | The Individual Brain Charting (IBC) project aims at providing a new generation of functional-brain atlases. To map cognitive mechanisms in a fine scale, task-fMRI data at high-spatial-resolution are being acquired on a fixed cohort of 12 participants, while performing many different tasks. These data—free from both int... | Provide a detailed description of the following dataset: IBC |
MICCAI 2015 Multi-Atlas Abdomen Labeling Challenge | Under Institutional Review Board (IRB) supervision, 50 abdomen CT scans of were randomly selected from a combination of an ongoing colorectal cancer chemotherapy trial, and a retrospective ventral hernia study. The 50 scans were captured during portal venous contrast phase with variable volume sizes (512 x 512 x 85 - 5... | Provide a detailed description of the following dataset: MICCAI 2015 Multi-Atlas Abdomen Labeling Challenge |
Alchemy | The DeepMind Alchemy environment is a meta-reinforcement learning benchmark that presents tasks sampled from a task distribution with deep underlying structure. It was created to test for the ability of agents to reason and plan via latent state inference, as well as useful exploration and experimentation.
Alchemy ... | Provide a detailed description of the following dataset: Alchemy |
Biase et al | Source: [Cell fate inclination within 2-cell and 4-cell mouse embryos revealed by single-cell RNA sequencing](https://pubmed.ncbi.nlm.nih.gov/25096407/) | Provide a detailed description of the following dataset: Biase et al |
Goolam et al | Source: [Heterogeneity in Oct4 and Sox2 Targets Biases Cell Fate in 4-Cell Mouse Embryos](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4819611/) | Provide a detailed description of the following dataset: Goolam et al |
Yan et al | Source: [Single-cell RNA-Seq profiling of human preimplantation embryos and embryonic stem cells](https://pubmed.ncbi.nlm.nih.gov/23934149/) | Provide a detailed description of the following dataset: Yan et al |
Deng et al | Source: [Single-cell RNA-seq reveals dynamic, random monoallelic gene expression in mammalian cells](https://pubmed.ncbi.nlm.nih.gov/24408435/) | Provide a detailed description of the following dataset: Deng et al |
Pollen et al | TPM values together with cell type annotations that were obtained from Alex Pollen on 15/10/15 | Provide a detailed description of the following dataset: Pollen et al |
Treutlein et al | Source: [Reconstructing lineage hierarchies of the distal lung epithelium using single-cell RNA-seq](https://pubmed.ncbi.nlm.nih.gov/24739965/) | Provide a detailed description of the following dataset: Treutlein et al |
Synthetic Rain Datasets | The Synthetic Rain Datasets consists of 13,712 clean-rain image pairs gathered from multiple datasets (Rain14000, Rain1800, Rain800, Rain12). With a single trained model, evaluation could be performed on various test sets, including Rain100H, Rain100L, Test100, Test2800, and Test1200.
PSNR and SSIM are computed on Y... | Provide a detailed description of the following dataset: Synthetic Rain Datasets |
EPIC-KITCHENS-100 | This paper introduces the pipeline to scale the largest dataset in egocentric vision EPIC-KITCHENS. The effort culminates in EPIC-KITCHENS-100, a collection of 100 hours, 20M frames, 90K actions in 700 variable-length videos, capturing long-term unscripted activities in 45 environments, using head-mounted cameras. Comp... | Provide a detailed description of the following dataset: EPIC-KITCHENS-100 |
UAVDT | UAVDT is a large scale challenging UAV Detection and Tracking benchmark (i.e., about 80, 000 representative frames from 10 hours raw videos) for 3 important fundamental tasks, i.e., object DETection
(DET), Single Object Tracking (SOT) and Multiple Object Tracking (MOT).
The dataset is captured by UAVs in various co... | Provide a detailed description of the following dataset: UAVDT |
The Contextual TV Dataset | Using the Experience-Sampling Method (ESM), participants are asked to report TV consumption multiple times each day for a five week period. Through self-reported data, authors decrease uncertainty of exposure to content, and allow collection of non-trivial information, such as how much attention is paid to the TV. The ... | Provide a detailed description of the following dataset: The Contextual TV Dataset |
twitter politicians data | Dataset based on Twitter usernames of American politicians. Data extracted from Wikidata.
The same politician can appear several times: if he has different pseudonyms on Twitter or Instagram, if he has been in several parties, or if several Twitter account IDs are associated with him. But the data is sorted in ascen... | Provide a detailed description of the following dataset: twitter politicians data |
CoNLL-2012 | The CoNLL-2012 shared task involved predicting coreference in English, Chinese, and Arabic, using the final version, v5.0, of the OntoNotes corpus. It was a follow-on to the English-only task organized in 2011. | Provide a detailed description of the following dataset: CoNLL-2012 |
3D Platelet EM | The platelet-em dataset contains two 3D scanning electron microscope (EM) images of human platelets, as well as instance and semantic segmentations of those two image volumes.
This data has been reviewed by NIBIB, contains no PII or PHI, and is cleared for public release. All files use a multipage uint16 TIF format. A... | Provide a detailed description of the following dataset: 3D Platelet EM |
Sintel 4D LFV | A medium-scale synthetic 4D Light Field video dataset for depth (disparity) estimation. From the open-source movie Sintel. The dataset consists of 24 synthetic 4D LFVs with 1,204x436 pixels, 9x9 views, and 20–50 frames, and has ground-truth disparity values, so that can be used for training deep learning-based methods.... | Provide a detailed description of the following dataset: Sintel 4D LFV |
Bee4Exp Honeybee Detection | A dataset for flying honeybee detection introduced in ["A Method for Detection of Small Moving Objects in UAV Videos"](https://www.mdpi.com/2072-4292/13/4/653).
This dataset consists of three videos with flying honeybees in a natural environment. | Provide a detailed description of the following dataset: Bee4Exp Honeybee Detection |
MHSMA | The MHSMA dataset is a collection of human sperm images from 235 patients with male factor infertility. Each image is labeled by experts for normal or abnormal sperm acrosome, head, vacuole, and tail.
The training, validation, and test sets contain 1000, 240, and 300 images, respectively.
Images are available in ... | Provide a detailed description of the following dataset: MHSMA |
VITON | VITON was a dataset for virtual try-on of clothing items. It consisted of 16,253 pairs of images of a person and a clothing item .
The authors have removed the dataset and it is no longer publicly available due to copyright issues. | Provide a detailed description of the following dataset: VITON |
Metric-Type of Numerical Tables | **Metric-Type of Numerical Tables** is a dataset extracted from scientific papers (ACL anthology website) consisting of header tables, captions, and metric-types.
Image source: [Suadaa et al.](https://arxiv.org/pdf/2102.00819v1.pdf) | Provide a detailed description of the following dataset: Metric-Type of Numerical Tables |
Deeply vocal characterizer | Deeply vocal characterizer is a human nonverbal vocalization dataset. This sample dataset consists of about 0.6 hours(56.7 hours in the full set) of audio(16 kHz, 16-bit, mono) across 16 human nonverbal vocalization classes, including throat-clearing, coughing, laughing, panting, and etc. The audio contents are crowdso... | Provide a detailed description of the following dataset: Deeply vocal characterizer |
Deeply Korean read speech | Deeply Korean read speech corpus contains pairs of Korean speakers reading a script with *__3 distinct text sentiments (negative, neutral, positive)__*, with *__3 distinct voice sentiments (negative, neutral, positive)__*, are recorded. The recordings took place in *__3 different types of places__*, which are *an anech... | Provide a detailed description of the following dataset: Deeply Korean read speech |
Deeply Parent-Child vocal interaction | Deeply Parent-Child Vocal Interaction contains the interaction of 24 pairs of parent and child(total 48 speakers), such as *__reading fairy tales, singing children’s songs, conversing, and others__*, is recorded. The recordings took place in *__3 different types of places__*, which are *an anechoic chamber, studio apar... | Provide a detailed description of the following dataset: Deeply Parent-Child vocal interaction |
Lesion Boundary Segmentation Dataset | Lesion Boundary Segmentation Dataset is a dataset for lesion segmentation from the ISIC2018 challenge. The dataset contains skin lesions and their corresponding annotations.
Image source :[]() | Provide a detailed description of the following dataset: Lesion Boundary Segmentation Dataset |
HOC | The **Hallmarks of Cancer** (**HOC*) corpus consists of 1852 PubMed publication abstracts manually annotated by experts according to the Hallmarks of Cancer taxonomy. The taxonomy consists of 37 classes in a hierarchy. Zero or more class labels are assigned to each sentence in the corpus. | Provide a detailed description of the following dataset: HOC |
MIT-BIH AFDB | This database includes 25 long-term ECG recordings of human subjects with atrial fibrillation (mostly paroxysmal).
Of these, 23 records include the two ECG signals (in the .dat files); records 00735 and 03665 are represented only by the rhythm (.atr) and unaudited beat (.qrs annotation files.
The individual recor... | Provide a detailed description of the following dataset: MIT-BIH AFDB |
ARC-DA | **ARC Direct Answer Questions** (**ARC-DA**) dataset consists of 2,985 grade-school level, direct-answer ("open response", "free form") science questions derived from the ARC multiple-choice question set released as part of the AI2 Reasoning Challenge in 2018.
### How the dataset was built
These questions were deri... | Provide a detailed description of the following dataset: ARC-DA |
Switchboard-1 Corpus | The Switchboard-1 Telephone Speech Corpus (LDC97S62) consists of approximately 260 hours of speech and was originally collected by Texas Instruments in 1990-1, under DARPA sponsorship. The first release of the corpus was published by NIST and distributed by the LDC in 1992-3.
Switchboard is a collection of about 2,4... | Provide a detailed description of the following dataset: Switchboard-1 Corpus |
MRDA | The **MRDA** corpus consists of about 75 hours of speech from 75 naturally-occurring meetings among 53 speakers. The tagset used for labeling is a modified version of the SWBD-DAMSL tagset. It is annotated with three types of information: marking of the dialogue act segment boundaries, marking of the dialogue acts and ... | Provide a detailed description of the following dataset: MRDA |
CLEVR-Humans | We collect a new dataset of human-posed free-form natural language questions about CLEVR images. Many of these questions have out-of-vocabulary words and require reasoning skills that are absent from our model’s repertoire | Provide a detailed description of the following dataset: CLEVR-Humans |
Funcom | Funcom is a collection of ~2.1 million Java methods and their associated Javadoc comments. This data set was derived from a set of 51 million Java methods and only includes methods that have an associated comment, comments that are in the English language, and has had auto-generated files removed. Each method/comment p... | Provide a detailed description of the following dataset: Funcom |
Synthetic and Real Apache Log Records | Each file contains a specific dataset described in the [paper](https://arxiv.org/abs/2102.06320) "On Automatic Parsing of Log Records". For example, `T_E.txt` contains the data for the dataset $T_E$.
In a file, each log string resides on a separate line and contains a 2-tuple separated by tab (`\t`). The first elem... | Provide a detailed description of the following dataset: Synthetic and Real Apache Log Records |
COVID-19 Fake News Dataset | Along with COVID-19 pandemic we are also fighting an `infodemic'. Fake news and rumors are rampant on social media. Believing in rumors can cause significant harm. This is further exacerbated at the time of a pandemic. To tackle this, we curate and release a manually annotated dataset of 10,700 social media posts and a... | Provide a detailed description of the following dataset: COVID-19 Fake News Dataset |
Real Blur Dataset | The dataset consists of 4,738 pairs of images of 232 different scenes including reference pairs. All images were captured both in the camera raw and JPEG formats, hence generating two datasets: RealBlur-R from the raw images, and RealBlur-J from the JPEG images. Each training set consists of 3,758 image pairs, while ea... | Provide a detailed description of the following dataset: Real Blur Dataset |
IG-3.5B-17k | **IG-3.5B-17k** is an internal Facebook AI Research dataset for training image classification models. It consists of hashtags for up to 3.5 billion public Instagram images. | Provide a detailed description of the following dataset: IG-3.5B-17k |
IG-1B-Targeted | **IG-1B-Targeted** is an internal Facebook AI Research dataset that consists of 940 million public images with 1.5K hashtags matching with 1000 ImageNet1K synsets. | Provide a detailed description of the following dataset: IG-1B-Targeted |
DAGM2007 | This is a synthetic dataset for defect detection on textured surfaces. It was originally created for a competition at the 2007 symposium of the DAGM (Deutsche Arbeitsgemeinschaft für Mustererkennung e.V., the German chapter of the International Association for Pattern Recognition). The competition was hosted together w... | Provide a detailed description of the following dataset: DAGM2007 |
DSTC 8 Track 2 | Dialog System Technology Challenges 8 (DSTC) Track 2 builds on the success of DSTC 7 Track 1 (NOESIS: Noetic End-to-End Response Selection Challenge). It proposes an extension of the task, incorporating new elements that are vital for the creation of a deployed task-oriented dialogue system. Specifically, three new dim... | Provide a detailed description of the following dataset: DSTC 8 Track 2 |
Ubuntu Chat Corpus | The **Ubuntu Chat Corpus** (**UCC**) is composed of archived chat logs from Ubuntu's Internet Relay Chat technical support channels. Ubuntu uses IRC as one of many modes of technical support -- it offers real-time problem solving. The authors have taken some of the archived messages (which are in the public domain), re... | Provide a detailed description of the following dataset: Ubuntu Chat Corpus |
Liu et al. Corpus | The **Liu et al. Corpus** is a pretraining dataset for large language models. It consists of 160Gb of news, books, stories, and web text. | Provide a detailed description of the following dataset: Liu et al. Corpus |
OSCAR | **OSCAR** or Open Super-large Crawled ALMAnaCH coRpus is a huge multilingual corpus obtained by language classification and filtering of the Common Crawl corpus using the goclassy architecture. The dataset used for training multilingual models such as BART incorporates 138 GB of text. | Provide a detailed description of the following dataset: OSCAR |
S-SOD | To validate the generalization abilities of SOD models, we create a small-scale dataset by collecting the most challenging images with varying brightness and contrast, background and foreground colors overlap, among many others. We conclude that the current models, including ours, are not trust-worthy for real-world pr... | Provide a detailed description of the following dataset: S-SOD |
Reddit Corpus | **Reddit Corpus** is part of a repository of conversational datasets consisting of hundreds of millions of examples, and a standardised evaluation procedure for conversational response selection models using '1-of-100 accuracy'. The Reddit Corpus contains 726 million multi-turn dialogues from the Reddit board. | Provide a detailed description of the following dataset: Reddit Corpus |
Advising Corpus | Advising Corpus is a dataset based on an entirely new collection of dialogues in which university students are being advised which classes to take. These were collected at the University of Michigan with IRB approval. They were released as part of DSTC 7 track 1 and used again in DSTC 8 track 2. | Provide a detailed description of the following dataset: Advising Corpus |
CCNet | CCNet is a dataset extracted from Common Crawl with a different filtering process than for OSCAR. It was built using a language model trained on Wikipedia, in order to filter out bad quality texts such as code or tables. CCNet contains longer documents on average compared to OSCAR with smaller—and often noisier—documen... | Provide a detailed description of the following dataset: CCNet |
French Wikipedia | **French Wikipedia** is a dataset used for pretraining the CamemBERT French language model. It uses the official 2019 French Wikipedia dumps | Provide a detailed description of the following dataset: French Wikipedia |
CEDAR Signature | CEDAR Signature is a database of off-line signatures for signature verification. Each of 55 individuals contributed 24 signatures thereby creating 1,320 genuine signatures. Some were asked to forge three other writers’ signatures, eight times
per subject, thus creating 1,320 forgeries. Each signature was scanned at 30... | Provide a detailed description of the following dataset: CEDAR Signature |
BanglaLekhaImageCaptions | This dataset consists of images and annotations in Bengali. The images are human annotated in Bengali by two adult native Bengali speakers. All popular image captioning datasets have a predominant western cultural bias with the annotations done in English. Using such datasets to train an image captioning system assumes... | Provide a detailed description of the following dataset: BanglaLekhaImageCaptions |
Multi-Domain Sentiment Dataset v2.0 | The Multi-Domain Sentiment Dataset contains product reviews taken from Amazon.com from many product types (domains). Some domains (books and dvds) have hundreds of thousands of reviews. Others (musical instruments) have only a few hundred. Reviews contain star ratings (1 to 5 stars) that can be converted into binary la... | Provide a detailed description of the following dataset: Multi-Domain Sentiment Dataset v2.0 |
PAQ | **Probably Asked Questions** (**PAQ**) is a very large resource of 65M automatically-generated QA-pairs. PAQ is a semi-structured Knowledge Base (KB) of 65M natural language QA-pairs, which models can memorise and/or learn to retrieve from. PAQ differs from traditional KBs in that questions and answers are stored in na... | Provide a detailed description of the following dataset: PAQ |
BABEL Project | **BABEL** is a multilingual corpus of conversational telephone speech from IARPA, which includes Asian and African languages. | Provide a detailed description of the following dataset: BABEL Project |
AIDA CoNLL-YAGO | **AIDA CoNLL-YAGO** contains assignments of entities to the mentions of named entities annotated for the original [CoNLL 2003 entity recognition task](https://www.clips.uantwerpen.be/conll2003/ner/). The entities are identified by YAGO2 entity name, by Wikipedia URL, or by Freebase mid. | Provide a detailed description of the following dataset: AIDA CoNLL-YAGO |
BTFDBB | Reflectance measurements of Bidirectional Texture Functions (BTFs)
Database contains both flat samples:
as well as 3D ge... | Provide a detailed description of the following dataset: BTFDBB |
CoNLL-2014 Shared Task: Grammatical Error Correction | CoNLL-2014 will continue the CoNLL tradition of having a high profile shared task in natural language processing. This year's shared task will be grammatical error correction, a continuation of the CoNLL shared task in 2013. A participating system in this shared task is given short English texts written by non-native s... | Provide a detailed description of the following dataset: CoNLL-2014 Shared Task: Grammatical Error Correction |
UBOFAB19 | A database of several hundred high quality fabric material measurements, provided as carefully calibrated rectified HDR images, together with SVBRDF fits.
... | Provide a detailed description of the following dataset: UBOFAB19 |
APPBENCH | A database of 56 high quality fabric material measurements, provided as carefully calibrated rectified HDR images, together with SVBRDF fits. Used in the [Fabric Appearance Challange](https://competitions.codalab.org/competitions/24979).
 cases from Hungary. It can be used as a longitudinal dataset for benchmarking the predictive performance of spatiotemporal graph neural network architectures. The dataset consists of a county-level adjacency matrix and... | Provide a detailed description of the following dataset: Chickenpox Cases in Hungary |
Multimodal Opinionlevel Sentiment Intensity | Multimodal Opinionlevel Sentiment Intensity (MOSI) contains: (1) multimodal observations including transcribed speech and visual gestures as well as automatic audio and visual features, (2) opinion-level subjectivity segmentation, (3) sentiment intensity annotations with high coder agreement, and (4) alignment between ... | Provide a detailed description of the following dataset: Multimodal Opinionlevel Sentiment Intensity |
WNUT 2017 | This shared task focuses on identifying unusual, previously-unseen entities in the context of emerging discussions. Named entities form the basis of many modern approaches to other tasks (like event clustering and summarisation), but recall on them is a real problem in noisy text - even among annotators. This drop tend... | Provide a detailed description of the following dataset: WNUT 2017 |
RUSHOLD | RUHSOLD is hate speech and offensive language dataset in Roman Urdu. The dataset contains over 10 thousand tweets that are hand labelled into the following categories:
1) Abusive/Offensive
2) Untargeted
3) Sexism
4) Religious
5) Neutral | Provide a detailed description of the following dataset: RUSHOLD |
Word Sense Disambiguation: a Unified Evaluation Framework and Empirical Comparison | The Evaluation framework of Raganato et al. 2017 includes two training sets (SemCor-Miller et al., 1993- and OMSTI-Taghipour and Ng, 2015-) and five test sets from the Senseval/SemEval series (Edmonds and Cotton, 2001; Snyder and Palmer, 2004; Pradhan et al., 2007; Navigli et al., 2013; Moro and Navigli, 2015), standar... | Provide a detailed description of the following dataset: Word Sense Disambiguation: a Unified Evaluation Framework and Empirical Comparison |
PNT | **The Parsing Time Normalizations** (**PNT**) corpus in SCATE format allows the representation of a wider variety of time expressions than previous approaches. This corpus was release with SemEval 2018 Task 6. | Provide a detailed description of the following dataset: PNT |
SemEval-2018 Task 9: Hypernym Discovery | The SemEval-2018 hypernym discovery evaluation benchmark (Camacho-Collados et al. 2018) contains three domains (general, medical and music) and is also available in Italian and Spanish (not in this repository). For each domain a target corpus and vocabulary (i.e. hypernym search space) are provided. The dataset contain... | Provide a detailed description of the following dataset: SemEval-2018 Task 9: Hypernym Discovery |
WHU-Specular dataset | WHU-Specular is a large dataset of annotated specular highlight regions created from real-world images. It can be used for specular highlight detection task. It contains 4310 image pairs (specular images and corresponding highlight masks). We randomly selected 3,017 images as the training set, and other 1293 images as ... | Provide a detailed description of the following dataset: WHU-Specular dataset |
NAB | **The First Temporal Benchmark Designed to Evaluate Real-time Anomaly Detectors Benchmark**
The growth of the Internet of Things has created an abundance of streaming data. Finding anomalies in this data can provide valuable insights into opportunities or failures. Yet it’s difficult to achieve, due to the need to ... | Provide a detailed description of the following dataset: NAB |
AVSpeech | **AVSpeech** is a large-scale audio-visual dataset comprising
speech clips with no interfering background signals. The segments
are of varying length, between 3 and 10 seconds long, and in each clip
the only visible face in the video and audible sound in the soundtrack
belong to a single speaking person. In total, ... | Provide a detailed description of the following dataset: AVSpeech |
Kinect-WSJ | Kinect-WSJ is a multichannel, multispeaker, reverberated, noisy dataset which extends the [WSJ0-2mix](/dataset/wsj0-2mix-1) singlechannel, non-reverberated, noiseless dataset to the strong reverberation and noise conditions and the Kinect-like microphone array geometry used in [CHiME-5](/dataset/chime-5). | Provide a detailed description of the following dataset: Kinect-WSJ |
BiasBios | The purpose of this dataset was to study gender bias in occupations. Online biographies, written in English, were collected to find the names, pronouns, and occupations. Twenty-eight most frequent occupations were identified based on their appearances. The resulting dataset consists of 397,340 biographies spanning twe... | Provide a detailed description of the following dataset: BiasBios |
BG-20k | BG-20k contains 20,000 high-resolution background images excluded salient objects, which can be used to help generate high quality synthetic data. | Provide a detailed description of the following dataset: BG-20k |
SPoC | Pseudocode-to-Code (SPoC) is a program synthesis dataset, containing 18,356 programs with human-authored pseudocode and test cases.
Image source: [https://sumith1896.github.io/spoc/](https://sumith1896.github.io/spoc/) | Provide a detailed description of the following dataset: SPoC |
OntoNotes 5.0 | **OntoNotes 5.0** is a large corpus comprising various genres of text (news, conversational telephone speech, weblogs, usenet newsgroups, broadcast, talk shows) in three languages (English, Chinese, and Arabic) with structural information (syntax and predicate argument structure) and shallow semantics (word sense linke... | Provide a detailed description of the following dataset: OntoNotes 5.0 |
WebText | **WebText** is an internal OpenAI corpus created by scraping web pages with emphasis on
document quality. The authors scraped all outbound links from
Reddit which received at least 3
karma. The authors used the approach as a heuristic indicator for
whether other users found the link interesting, educational,
or ju... | Provide a detailed description of the following dataset: WebText |
MECCANO | The MECCANO dataset is the first dataset of egocentric videos to study human-object interactions in industrial-like settings.
The MECCANO dataset has been acquired in an industrial-like scenario in which subjects built a toy model of a motorbike. We considered 20 object classes which include the 16 classes categorizin... | Provide a detailed description of the following dataset: MECCANO |
ecoset | **Ecoset**, an ecologically motivated image dataset, is a large-scale image dataset designed for human visual neuroscience, which consists of over 1.5 million images from 565 basic-level categories. Category selection was based on English nouns that most frequently occur in spoken language (estimated on a set of 51 mil... | Provide a detailed description of the following dataset: ecoset |
CoNLL 2003 | **CoNLL-2003** is a named entity recognition dataset released as a part of CoNLL-2003 shared task: language-independent named entity recognition.
The data consists of eight files covering two languages: English and German.
For each of the languages there is a training file, a development file, a test file and a large... | Provide a detailed description of the following dataset: CoNLL 2003 |
QAMR | **Question-Answer Meaning Representation** (**QAMR**) represents a predicate-argument structure of a sentence with a set of question-answer pairs, so that annotations can be easily provided by non-experts. QAMR is a dataset of over 5,000 sentences and 100,000 questions created by crowdsourcing workers. | Provide a detailed description of the following dataset: QAMR |
AW-OIE | **All Words Open IE** (**AW-OIE**) is an open information extraction dataset derived from [Question-Answer Meaning Representation (QAMR)](/dataset/qamr) dataset. | Provide a detailed description of the following dataset: AW-OIE |
MSU Deinterlacer Benchmark | This is a dataset for video deinterlacing problem. The dataset contains 40 video sequences. Each sequence's length is 1 second. Resolution of all video sequences is 1920x1080. FPS varies from 24 to 60. TFF interlacing was used to get interlaced data from GT. | Provide a detailed description of the following dataset: MSU Deinterlacer Benchmark |
StrategyQA | **StrategyQA** is a question answering benchmark where the required reasoning steps are implicit in the question, and should be inferred using a strategy.
It includes 2,780 examples, each consisting of a strategy question, its decomposition, and evidence paragraphs.
Questions in StrategyQA are short, topic-diverse, a... | Provide a detailed description of the following dataset: StrategyQA |
Oxford 102 Flower | **Oxford 102 Flower** is an image classification dataset consisting of 102 flower categories. The flowers chosen to be flower commonly occurring in the United Kingdom. Each class consists of between 40 and 258 images.
The images have large scale, pose and light variations. In addition, there are categories that have... | Provide a detailed description of the following dataset: Oxford 102 Flower |
ICB | A carefully chosen set of high-resolution high-precision natural images suited for compression algorithm evaluation.
The images historically used for compression research (lena, barbra, pepper etc...) have outlived their useful life and its about time they become a part of history only. They are too small, come from... | Provide a detailed description of the following dataset: ICB |
LIVE1 | Quality Assessment research strongly depends upon subjective experiments to provide calibration data as well as a testing mechanism. After all, the goal of all QA research is to make quality predictions that are in agreement with subjective opinion of human observers. In order to calibrate QA algorithms and test their ... | Provide a detailed description of the following dataset: LIVE1 |
Classic5 | Five classic grayscale images commonly used for image quality assessment tasks. | Provide a detailed description of the following dataset: Classic5 |
hls4ml LHC Jet dataset | Dataset of high-pT jets from simulations of LHC proton-proton collisions
Prepared for FastML/HLS4ML studies: https://fastmachinelearning.org
Includes: High level features (see https://arxiv.org/abs/1804.06913)
Images: jet images with up to 100 particles/jet (see https://arxiv.org/abs/1908.05318)
List: list ... | Provide a detailed description of the following dataset: hls4ml LHC Jet dataset |
RailEye3D Dataset | The RailEye3D dataset, a collection of train-platform scenarios for applications targeting passenger safety and automation of train dispatching, consists of 10 image sequences captured at 6 railway stations in Austria. Annotations for multi-object tracking are provided in both an unified format as well as the ground-tr... | Provide a detailed description of the following dataset: RailEye3D Dataset |
GraspNet-1Billion | **GraspNet-1Billion** provides large-scale training data and a standard evaluation platform for the task of general robotic grasping. The dataset contains 97,280 RGB-D image with over one billion grasp poses. | Provide a detailed description of the following dataset: GraspNet-1Billion |
MAEC | **MAEC** is a new, large-scale multi-modal, text-audio paired, earnings-call dataset named MAEC, based on S&P 1500 companies. | Provide a detailed description of the following dataset: MAEC |
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