dataset_name stringlengths 2 128 | description stringlengths 1 9.7k | prompt stringlengths 59 185 |
|---|---|---|
ActivityNet Captions | The **ActivityNet Captions** dataset is built on ActivityNet v1.3 which includes 20k YouTube untrimmed videos with 100k caption annotations. The videos are 120 seconds long on average. Most of the videos contain over 3 annotated events with corresponding start/end time and human-written sentences, which contain 13.5 wo... | Provide a detailed description of the following dataset: ActivityNet Captions |
smallNORB | The **smallNORB** dataset is a datset for 3D object recognition from shape. It contains images of 50 toys belonging to 5 generic categories: four-legged animals, human figures, airplanes, trucks, and cars. The objects were imaged by two cameras under 6 lighting conditions, 9 elevations (30 to 70 degrees every 5 degrees... | Provide a detailed description of the following dataset: smallNORB |
DocRED | **DocRED** (Document-Level Relation Extraction Dataset) is a relation extraction dataset constructed from Wikipedia and Wikidata. Each document in the dataset is human-annotated with named entity mentions, coreference information, intra- and inter-sentence relations, and supporting evidence. DocRED requires reading mul... | Provide a detailed description of the following dataset: DocRED |
iMaterialist | Constructed from over one million fashion images with a label space that includes 8 groups of 228 fine-grained attributes in total. Each image is annotated by experts with multiple, high-quality fashion attributes. | Provide a detailed description of the following dataset: iMaterialist |
ImageNet-C | **ImageNet-C** is an open source data set that consists of algorithmically generated corruptions (blur, noise) applied to the ImageNet test-set. | Provide a detailed description of the following dataset: ImageNet-C |
ImageNet-A | The **ImageNet-A** dataset consists of real-world, unmodified, and naturally occurring examples that are misclassified by ResNet models. | Provide a detailed description of the following dataset: ImageNet-A |
BIOSSES | The BIOSSES data set comprises total 100 sentence pairs all of which were selected from the "[TAC2 Biomedical Summarization Track Training Data Set](https://tac.nist.gov/2014/BiomedSumm/)" .
The sentence pairs were evaluated by five different human experts that judged their similarity and gave scores in a range [0-4... | Provide a detailed description of the following dataset: BIOSSES |
MedNLI | The **MedNLI** dataset consists of the sentence pairs developed by Physicians from the Past Medical History section of MIMIC-III clinical notes annotated for Definitely True, Maybe True and Definitely False. The dataset contains 11,232 training, 1,395 development and 1,422 test instances. This provides a natural langua... | Provide a detailed description of the following dataset: MedNLI |
UCF-QNRF | The **UCF-QNRF** dataset is a crowd counting dataset and it contains large diversity both in scenes, as well as in background types. It consists of 1535 images high-resolution images from Flickr, Web Search and Hajj footage. The number of people (i.e., the count) varies from 50 to 12,000 across images. | Provide a detailed description of the following dataset: UCF-QNRF |
WiderPerson | WiderPerson contains a total of 13,382 images with 399,786 annotations, i.e., 29.87 annotations per image, which means this dataset contains dense pedestrians with various kinds of occlusions. Hence, pedestrians in the proposed dataset are extremely challenging due to large variations in the scenario and occlusion, whi... | Provide a detailed description of the following dataset: WiderPerson |
CID | The **CID** (**Campus Image Dataset**) is a dataset captured in low-light env with the help of Android programming. Its basic unit is group, which is named by capture time and contains 8 exposure-time-varying raw image shot in a burst.
Source: [https://github.com/505030475/ExtremeLowLight](https://github.com/505030475... | Provide a detailed description of the following dataset: CID |
LeNER-Br | LeNER-Br is a dataset for named entity recognition (NER) in Brazilian Legal Text. | Provide a detailed description of the following dataset: LeNER-Br |
DAVIS | The Densely Annotation Video Segmentation dataset (**DAVIS**) is a high quality and high resolution densely annotated video segmentation dataset under two resolutions, 480p and 1080p. There are 50 video sequences with 3455 densely annotated frames in pixel level. 30 videos with 2079 frames are for training and 20 video... | Provide a detailed description of the following dataset: DAVIS |
VIST | The **Visual Storytelling** Dataset (**VIST**) consists of 210,819 unique photos and 50,000 stories. The images were collected from albums on Flickr. The albums included 10 to 50 images and all the images in an album are taken in a 48-hour span. The stories were created by workers on Amazon Mechanical Turk, where the w... | Provide a detailed description of the following dataset: VIST |
DTD | The **Describable Textures Dataset** (**DTD**) contains 5640 texture images in the wild. They are annotated with human-centric attributes inspired by the perceptual properties of textures. | Provide a detailed description of the following dataset: DTD |
Adience | The **Adience** dataset, published in 2014, contains 26,580 photos across 2,284 subjects with a binary gender label and one label from eight different age groups, partitioned into five splits. The key principle of the data set is to capture the images as close to real world conditions as possible, including all variati... | Provide a detailed description of the following dataset: Adience |
Matterport3D | The **Matterport3D** dataset is a large RGB-D dataset for scene understanding in indoor environments. It contains 10,800 panoramic views inside 90 real building-scale scenes, constructed from 194,400 RGB-D images. Each scene is a residential building consisting of multiple rooms and floor levels, and is annotated with ... | Provide a detailed description of the following dataset: Matterport3D |
OIE2016 | OIE2016 is the first large-scale OpenIE benchmark. It is created by automatic conversion from QA-SRL [He et al., 2015], a semantic role labeling dataset. The sentences are from news (e.g., WSJ) and encyclopedia (e.g., WIKI) domains. Since there are no restrictions on the elements of OpenIE extractions, partial-matching... | Provide a detailed description of the following dataset: OIE2016 |
ToTTo | ToTTo is an open-domain English table-to-text dataset with over 120,000 training examples that proposes a controlled generation task: given a Wikipedia table and a set of highlighted table cells, produce a one-sentence description.
During the dataset creation process, tables from English Wikipedia are matched with (... | Provide a detailed description of the following dataset: ToTTo |
PCam | **PatchCamelyon** is an image classification dataset. It consists of 327.680 color images (96 x 96px) extracted from histopathologic scans of lymph node sections. Each image is annotated with a binary label indicating presence of metastatic tissue. PCam provides a new benchmark for machine learning models: bigger than ... | Provide a detailed description of the following dataset: PCam |
Kumar | The **Kumar** dataset contains 30 1,000×1,000 image tiles from seven organs (6 breast, 6 liver, 6 kidney, 6 prostate, 2 bladder, 2 colon and 2 stomach) of The Cancer Genome Atlas (TCGA) database acquired at 40× magnification. Within each image, the boundary of each nucleus is fully annotated. | Provide a detailed description of the following dataset: Kumar |
HellaSwag | HellaSwag is a challenge dataset for evaluating commonsense NLI that is specially hard for state-of-the-art models, though its questions are trivial for humans (>95% accuracy). | Provide a detailed description of the following dataset: HellaSwag |
LAMBADA | The **LAMBADA** (LAnguage Modeling Broadened to Account for Discourse Aspects) benchmark is an open-ended cloze task which consists of about 10,000 passages from BooksCorpus where a missing target word is predicted in the last sentence of each passage. The missing word is constrained to always be the last word of the l... | Provide a detailed description of the following dataset: LAMBADA |
PIQA | PIQA is a dataset for commonsense reasoning, and was created to investigate the physical knowledge of existing models in NLP. | Provide a detailed description of the following dataset: PIQA |
OpenBookQA | **OpenBookQA** is a new kind of question-answering dataset modeled after open book exams for assessing human understanding of a subject. It consists of 5,957 multiple-choice elementary-level science questions (4,957 train, 500 dev, 500 test), which probe the understanding of a small “book” of 1,326 core science facts a... | Provide a detailed description of the following dataset: OpenBookQA |
WSC | The **Winograd Schema Challenge** was introduced both as an alternative to the Turing Test and as a test of a system’s ability to do commonsense reasoning. A Winograd schema is a pair of sentences differing in one or two words with a highly ambiguous pronoun, resolved differently in the two sentences, that appears to r... | Provide a detailed description of the following dataset: WSC |
arXiv | **Arxiv HEP-TH (high energy physics theory) citation graph** is from the e-print **arXiv** and covers all the citations within a dataset of 27,770 papers with 352,807 edges. If a paper i cites paper j, the graph contains a directed edge from i to j. If a paper cites, or is cited by, a paper outside the dataset, the gra... | Provide a detailed description of the following dataset: arXiv |
ECE | The ECE dataset (Gui et al., 2016a) is collected from SINA city news and contains 2105 instances. Its document has only one emotion word and one or more emotion causes. | Provide a detailed description of the following dataset: ECE |
PhyAAt | The dataset contains a collection of physiological signals (EEG, GSR, PPG) obtained from an experiment of the auditory attention on natural speech. Ethical Approval was acquired for the experiment. Details of the experiment can be found here **[https://phyaat.github.io/experiment](https://phyaat.github.io/experiment)**... | Provide a detailed description of the following dataset: PhyAAt |
LEVIR-CD | LEVIR-CD is a new large-scale remote sensing building Change Detection dataset. The introduced dataset would be a new benchmark for evaluating change detection (CD) algorithms, especially those based on deep learning.
LEVIR-CD consists of 637 very high-resolution (VHR, 0.5m/pixel) Google Earth (GE) image patch pairs... | Provide a detailed description of the following dataset: LEVIR-CD |
FEVER | FEVER is a publicly available dataset for fact extraction and verification against textual sources.
It consists of 185,445 claims manually verified against the introductory sections of Wikipedia pages and classified as SUPPORTED, REFUTED or NOTENOUGHINFO. For the first two classes, systems and annotators need to als... | Provide a detailed description of the following dataset: FEVER |
MELD | **Multimodal EmotionLines Dataset** (**MELD**) has been created by enhancing and extending EmotionLines dataset. MELD contains the same dialogue instances available in EmotionLines, but it also encompasses audio and visual modality along with text. MELD has more than 1400 dialogues and 13000 utterances from Friends TV ... | Provide a detailed description of the following dataset: MELD |
EmoryNLP | EmoryNLP comprises 97 episodes, 897 scenes, and 12,606 utterances, where each utterance is annotated with one of the seven emotions borrowed from the six primary emotions in the Willcox (1982)’s feeling wheel, sad, mad, scared, powerful, peaceful, joyful, and a default emotion of neutral. | Provide a detailed description of the following dataset: EmoryNLP |
4D Light Field Dataset | 4D Light Field Dataset is a light field benchmark consisting of 24 carefully designed synthetic, densely sampled 4D
light fields with highly accurate disparity ground truth. | Provide a detailed description of the following dataset: 4D Light Field Dataset |
Virtual KITTI 2 | Virtual KITTI 2 is an updated version of the well-known Virtual KITTI dataset which consists of 5 sequence clones from the KITTI tracking benchmark. In addition, the dataset provides different variants of these sequences such as modified weather conditions (e.g. fog, rain) or modified camera configurations (e.g. rotate... | Provide a detailed description of the following dataset: Virtual KITTI 2 |
WHAMR! | **WHAMR!** is a dataset for noisy and reverberant speech separation. It extends [WHAM!](/dataset/wham) by introducing synthetic reverberation to the
speech sources in addition to the existing noise. Room impulse responses were generated and convolved using `pyroomacoustics`. Reverberation times were chosen to approxim... | Provide a detailed description of the following dataset: WHAMR! |
VoiceBank + DEMAND | VoiceBank+DEMAND is a noisy speech database for training speech enhancement algorithms and TTS models. The database was designed to train and test speech enhancement methods that operate at 48kHz. A more detailed description can be found in the paper associated with the database. Some of the noises were obtained from t... | Provide a detailed description of the following dataset: VoiceBank + DEMAND |
BUFF | **BUFF** consists of 5 subjects, 3 male and 2 female wearing 2 clothing styles: a) t-shirt and long pants and b) a soccer outfit.
They perform 3 different motions i) hips ii) tilt_twist_left iii) shoulders_mill. | Provide a detailed description of the following dataset: BUFF |
Taskonomy | Taskonomy provides a large and high-quality dataset of varied indoor scenes.
- Complete pixel-level geometric information via aligned meshes.
- Semantic information via knowledge distillation from ImageNet, MS COCO, and MIT Places.
- Globally consistent camera poses. Complete camera intrinsics.
- High-definition ... | Provide a detailed description of the following dataset: Taskonomy |
Abalone | Predicting the age of abalone from physical measurements. The age of abalone is determined by cutting the shell through the cone, staining it, and counting the number of rings through a microscope -- a boring and time-consuming task. Other measurements, which are easier to obtain, are used to predict the age. Further i... | Provide a detailed description of the following dataset: Abalone |
Letter | Letter Recognition Data Set is a handwritten digit dataset. The task is to identify each of a large number of black-and-white rectangular pixel displays as one of the 26 capital letters in the English alphabet. The character images were based on 20 different fonts and each letter within these 20 fonts was randomly dist... | Provide a detailed description of the following dataset: Letter |
Electricity | **Abstract**: Measurements of electric power consumption in one household with a one-minute sampling rate over a period of almost 4 years. Different electrical quantities and some sub-metering values are available.
| Data Set Characteristics | Number of Instances | Area | Attribute Characteristics | Number of A... | Provide a detailed description of the following dataset: Electricity |
NetHack Learning Environment | The **NetHack Learning Environment** (NLE) is a Reinforcement Learning environment based on NetHack 3.6.6. It is designed to provide a standard reinforcement learning interface to the game, and comes with tasks that function as a first step to evaluate agents on this new environment.
NetHack is one of the oldest and ar... | Provide a detailed description of the following dataset: NetHack Learning Environment |
Kvasir-SEG | Kvasir-SEG is an open-access dataset of gastrointestinal polyp images and corresponding segmentation masks, manually annotated by a medical doctor and then verified by an experienced gastroenterologist. | Provide a detailed description of the following dataset: Kvasir-SEG |
2018 Data Science Bowl | This dataset contains a large number of segmented nuclei images. The images were acquired under a variety of conditions and vary in the cell type, magnification, and imaging modality (brightfield vs. fluorescence). The dataset is designed to challenge an algorithm's ability to generalize across these variations.
Eac... | Provide a detailed description of the following dataset: 2018 Data Science Bowl |
CVC-ClinicDB | **CVC-ClinicDB** is an open-access dataset of 612 images with a resolution of 384×288 from 31 colonoscopy sequences.It is used for medical image segmentation, in particular polyp detection in colonoscopy videos.
Source: [ResUNet++: An Advanced Architecture for Medical Image Segmentation](https://arxiv.org/abs/1911.070... | Provide a detailed description of the following dataset: CVC-ClinicDB |
CAT2000 | Includes 4000 images; 200 from each of 20 categories covering different types of scenes such as Cartoons, Art, Objects, Low resolution images, Indoor, Outdoor, Jumbled, Random, and Line drawings. | Provide a detailed description of the following dataset: CAT2000 |
FixaTons | FixaTons is a large collection of datasets human scanpaths (temporally ordered sequences of fixations) and saliency maps. | Provide a detailed description of the following dataset: FixaTons |
ImageNet-R | ImageNet-R(endition) contains art, cartoons, deviantart, graffiti, embroidery, graphics, origami, paintings, patterns, plastic objects, plush objects, sculptures, sketches, tattoos, toys, and video game renditions of ImageNet classes.
ImageNet-R has renditions of 200 ImageNet classes resulting in 30,000 images. | Provide a detailed description of the following dataset: ImageNet-R |
20 Newsgroups | The 20 Newsgroups data set is a collection of approximately 20,000 newsgroup documents, partitioned (nearly) evenly across 20 different newsgroups. | Provide a detailed description of the following dataset: 20 Newsgroups |
HACS | HACS is a dataset for human action recognition. It uses a taxonomy of 200 action classes, which is identical to that of the ActivityNet-v1.3 dataset. It has 504K videos retrieved from YouTube. Each one is strictly shorter than 4 minutes, and the average length is 2.6 minutes. A total of 1.5M clips of 2-second duration ... | Provide a detailed description of the following dataset: HACS |
Kinetics-700 | Kinetics-700 is a video dataset of 650,000 clips that covers 700 human action classes. The videos include human-object interactions such as playing instruments, as well as human-human interactions such as shaking hands and hugging. Each action class has at least 700 video clips. Each clip is annotated with an action cl... | Provide a detailed description of the following dataset: Kinetics-700 |
Completion3D | The Completion3D benchmark is a dataset for evaluating state-of-the-art 3D Object Point Cloud Completion methods. Ggiven a partial 3D object point cloud the goal is to infer a complete 3D point cloud for the object. | Provide a detailed description of the following dataset: Completion3D |
QMNIST | The exact pre-processing steps used to construct the MNIST dataset have long been lost. This leaves us with no reliable way to associate its characters with the ID of the writer and little hope to recover the full MNIST testing set that had 60K images but was never released. The official MNIST testing set only contains... | Provide a detailed description of the following dataset: QMNIST |
ROCStories | **ROCStories** is a collection of commonsense short stories. The corpus consists of 100,000 five-sentence stories. Each story logically follows everyday topics created by Amazon Mechanical Turk workers. These stories contain a variety of commonsense causal and temporal relations between everyday events. Writers also de... | Provide a detailed description of the following dataset: ROCStories |
ePillID | **ePillID** is a benchmark for developing and evaluating computer vision models for pill identification. The ePillID benchmark is designed as a low-shot fine-grained benchmark, reflecting real-world challenges for developing image-based pill identification systems.
The characteristics of the ePillID benchmark include:
... | Provide a detailed description of the following dataset: ePillID |
CodeSearchNet | The **CodeSearchNet** Corpus is a large dataset of functions with associated documentation written in Go, Java, JavaScript, PHP, Python, and Ruby from open source projects on GitHub. The CodeSearchNet Corpus includes:
* Six million methods overall
* Two million of which have associated documentation (docstrings, Java... | Provide a detailed description of the following dataset: CodeSearchNet |
WikiTableQuestions | **WikiTableQuestions** is a question answering dataset over semi-structured tables. It is comprised of question-answer pairs on HTML tables, and was constructed by selecting data tables from Wikipedia that contained at least 8 rows and 5 columns. Amazon Mechanical Turk workers were then tasked with writing trivia quest... | Provide a detailed description of the following dataset: WikiTableQuestions |
AViD | Is a collection of action videos from many different countries. The motivation is to create a public dataset that would benefit training and pretraining of action recognition models for everybody, rather than making it useful for limited countries. | Provide a detailed description of the following dataset: AViD |
MTL-AQA | A new multitask action quality assessment (AQA) dataset, the largest to date, comprising of more than 1600 diving samples; contains detailed annotations for fine-grained action recognition, commentary generation, and estimating the AQA score. Videos from multiple angles provided wherever available. | Provide a detailed description of the following dataset: MTL-AQA |
AQA-7 | Consists of 1106 action samples from seven actions with quality scores as measured by expert human judges. | Provide a detailed description of the following dataset: AQA-7 |
AGENDA | Abstract GENeration DAtaset (AGENDA) is a dataset of knowledge graphs paired with scientific abstracts. The dataset consists of 40k paper titles and abstracts from the Semantic Scholar Corpus taken from the proceedings of 12 top AI conferences. | Provide a detailed description of the following dataset: AGENDA |
GoPro | The **GoPro** dataset for deblurring consists of 3,214 blurred images with the size of 1,280×720 that are divided into 2,103 training images and 1,111 test images. The dataset consists of pairs of a realistic blurry image and the corresponding ground truth shapr image that are obtained by a high-speed camera. | Provide a detailed description of the following dataset: GoPro |
AMZ Computers | AMZ Computers is a co-purchase graph extracted from Amazon, where nodes represent products, edges represent the co-purchased relations of products, and features are bag-of-words vectors extracted from product reviews. | Provide a detailed description of the following dataset: AMZ Computers |
SVG-Icons8 | A new large-scale dataset along with an open-source library for SVG manipulation. | Provide a detailed description of the following dataset: SVG-Icons8 |
K2HPD | Includes 100K depth images under challenging scenarios. | Provide a detailed description of the following dataset: K2HPD |
Binarized MNIST | A binarized version of MNIST. | Provide a detailed description of the following dataset: Binarized MNIST |
CAMO | Camouflaged Object (CAMO) dataset specifically designed for the task of camouflaged object segmentation. We focus on two categories, i.e., naturally camouflaged objects and artificially camouflaged objects, which usually correspond to animals and humans in the real world, respectively. Camouflaged object images consist... | Provide a detailed description of the following dataset: CAMO |
CAS-VSR-W1k (LRW-1000) | *LRW-1000 has been renamed as CAS-VSR-W1k.** It is a naturally-distributed large-scale benchmark for word-level lipreading in the wild, including 1000 classes with about 718,018 video samples from more than 2000 individual speakers. There are more than 1,000,000 Chinese character instances in total. Each class correspo... | Provide a detailed description of the following dataset: CAS-VSR-W1k (LRW-1000) |
LRS2 | The Oxford-BBC **Lip Reading Sentences 2** (**LRS2**) dataset is one of the largest publicly available datasets for lip reading sentences in-the-wild. The database consists of mainly news and talk shows from BBC programs. Each sentence is up to 100 characters in length. The training, validation and test sets are divide... | Provide a detailed description of the following dataset: LRS2 |
PeMS04 | PeMS04 is a traffic forecasting benchmark. | Provide a detailed description of the following dataset: PeMS04 |
Moving MNIST | The **Moving MNIST** dataset contains 10,000 video sequences, each consisting of 20 frames. In each video sequence, two digits move independently around the frame, which has a spatial resolution of 64×64 pixels. The digits frequently intersect with each other and bounce off the edges of the frame | Provide a detailed description of the following dataset: Moving MNIST |
Sprites | The **Sprites** dataset contains 60 pixel color images of animated characters (sprites). There are 672 sprites, 500 for training, 100 for testing and 72 for validation. Each sprite has 20 animations and 178 images, so the full dataset has 120K images in total. There are many changes in the appearance of the sprites, th... | Provide a detailed description of the following dataset: Sprites |
Hyperpartisan News Detection | Hyperpartisan News Detection was a dataset created for PAN @ SemEval 2019 Task 4. Given a news article text, decide whether it follows a hyperpartisan argumentation, i.e., whether it exhibits blind, prejudiced, or unreasoning allegiance to one party, faction, cause, or person.
There are two parts:
* byarticle: La... | Provide a detailed description of the following dataset: Hyperpartisan News Detection |
BigPatent | Consists of 1.3 million records of U.S. patent documents along with human written abstractive summaries. | Provide a detailed description of the following dataset: BigPatent |
NoW Benchmark | The goal of this benchmark is to introduce a standard evaluation metric to measure the accuracy and robustness of 3D face reconstruction methods under variations in viewing angle, lighting, and common occlusions.
The dataset contains 2054 2D images of 100 subjects, captured with an iPhone X, and a separate 3D head ... | Provide a detailed description of the following dataset: NoW Benchmark |
WikiHow | **WikiHow** is a dataset of more than 230,000 article and summary pairs extracted and constructed from an online knowledge base written by different human authors. The articles span a wide range of topics and represent high diversity styles. | Provide a detailed description of the following dataset: WikiHow |
Tobacco-3482 | The Tobacco-3482 dataset consists of document images belonging to 10 classes such as letter, form, email, resume, memo, etc. The dataset has 3482 images. | Provide a detailed description of the following dataset: Tobacco-3482 |
Horse-10 | **Horse-10** is an animal pose estimation dataset. It comprises 30 diverse Thoroughbred horses, for which 22 body parts were labeled by an expert in *8,114* frames (animal pose estimation). Horses have various coat colors and the “in-the-wild” aspect of the collected data at various Thoroughbred yearling sales and farm... | Provide a detailed description of the following dataset: Horse-10 |
FreiHAND | **FreiHAND** is a 3D hand pose dataset which records different hand actions performed by 32 people. For each hand image, MANO-based 3D hand pose annotations are provided. It currently contains 32,560 unique training samples and 3960 unique samples for evaluation. The training samples are recorded with a green screen ba... | Provide a detailed description of the following dataset: FreiHAND |
DomainNet | **DomainNet** is a dataset of common objects in six different domain. All domains include 345 categories (classes) of objects such as Bracelet, plane, bird and cello. The domains include clipart: collection of clipart images; real: photos and real world images; sketch: sketches of specific objects; infograph: infograph... | Provide a detailed description of the following dataset: DomainNet |
Ethics | Ethics1 (sit ethics) dataset is created to test the knowledge of the basic concepts of morality. The task is to predict human ethical judgments about diverse text situations in a multi-label classification setting. Namely, the task requires models to identify the presence of concepts in normative ethics, such as virtue... | Provide a detailed description of the following dataset: Ethics |
Skeleton-Mimetics | A dataset derived from the recently introduced Mimetics dataset. | Provide a detailed description of the following dataset: Skeleton-Mimetics |
Universal Dependencies | The **Universal Dependencies** (UD) project seeks to develop cross-linguistically consistent treebank annotation of morphology and syntax for multiple languages. The first version of the dataset was released in 2015 and consisted of 10 treebanks over 10 languages. Version 2.7 released in 2020 consists of 183 treebanks ... | Provide a detailed description of the following dataset: Universal Dependencies |
TallyQA | TallyQA is a large-scale dataset for open-ended counting. | Provide a detailed description of the following dataset: TallyQA |
CrisisMMD | CrisisMMD is a large multi-modal dataset collected from Twitter during different natural disasters. It consists of several thousands of manually annotated tweets and images collected during seven major natural disasters including earthquakes, hurricanes, wildfires, and floods that happened in the year 2017 across diffe... | Provide a detailed description of the following dataset: CrisisMMD |
UAVA | The UAVA,<i>UAV-Assistant</i>, dataset is specifically designed for fostering applications which consider UAVs and humans as cooperative agents.
We employ a real-world 3D scanned dataset (<a href="https://niessner.github.io/Matterport/">Matterport3D</a>), physically-based rendering, a gamified simulator for realistic d... | Provide a detailed description of the following dataset: UAVA |
Panoptic | **CMU Panoptic** is a large scale dataset providing 3D pose annotations (1.5 millions) for multiple people engaging social activities. It contains 65 videos (5.5 hours) with multi-view annotations, but only 17 of them are in multi-person scenario and have the camera parameters.
**Massively Multiview System**
* ... | Provide a detailed description of the following dataset: Panoptic |
Set5 | The **Set5** dataset is a dataset consisting of 5 images (“baby”, “bird”, “butterfly”, “head”, “woman”) commonly used for testing performance of Image Super-Resolution models.
Image Source: [http://people.rennes.inria.fr/Aline.Roumy/results/SR_BMVC12.html](http://people.rennes.inria.fr/Aline.Roumy/results/SR_BMVC12.ht... | Provide a detailed description of the following dataset: Set5 |
ContactPose | ContactPose is a dataset of hand-object contact paired with hand pose, object pose, and RGB-D images. ContactPose has 2306 unique grasps of 25 household objects grasped with 2 functional intents by 50 participants, and more than 2.9 M RGB-D grasp images. | Provide a detailed description of the following dataset: ContactPose |
DHF1K | **DHF1K** is a video saliency dataset which contains a ground-truth map of binary pixel-wise gaze fixation points and a continuous map of the fixation points after being blurred by a gaussian filter. DHF1K contains 1000 videos in total. 700 of the videos are annotated, 600 of which are used for training and 100 for val... | Provide a detailed description of the following dataset: DHF1K |
How2 | The **How2** dataset contains 13,500 videos, or 300 hours of speech, and is split into 185,187 training, 2022 development (dev), and 2361 test utterances. It has subtitles in English and crowdsourced Portuguese translations. | Provide a detailed description of the following dataset: How2 |
ASSET | ASSET is a new dataset for assessing sentence simplification in English. ASSET is a crowdsourced multi-reference corpus where each simplification was produced by executing several rewriting transformations. | Provide a detailed description of the following dataset: ASSET |
TurkCorpus | TurkCorpus, a dataset with 2,359 original sentences from English Wikipedia, each with 8 manual reference simplifications.
The dataset is divided into two subsets: 2,000 sentences for validation and 359 for testing of sentence simplification models. | Provide a detailed description of the following dataset: TurkCorpus |
IRMA | This collection compiles anonymous radiographs, which have been arbitrarly selected from routine at the Department of Diagnostic Radiology, Aachen University of Technology (RWTH), Aachen, Germany. The imagery represents different ages, genders, view positions and pathologies. Therefore, image quality varies significant... | Provide a detailed description of the following dataset: IRMA |
MLFP | The **MLFP** dataset consists of face presentation attacks captured with seven 3D latex masks and three 2D print attacks. The dataset contains videos captured from color, thermal and infrared channels. | Provide a detailed description of the following dataset: MLFP |
CoNLL++ | CoNLL++ is a corrected version of the CoNLL03 NER dataset where 5.38% of the test sentences have been fixed. | Provide a detailed description of the following dataset: CoNLL++ |
ViSal | DataViSal.rar (including the ground truth data) is our new collected dataset for the following paper.
===========================================================================
W. Wang, J. Shen, and L. Shao,
Consistent video saliency using local gradient flow optimization and global refinement,
IEEE Trans. ... | Provide a detailed description of the following dataset: ViSal |
SOC | SOC (Salient Objects in Clutter) is a dataset for Salient Object Detection (SOD). It includes images with salient and non-salient objects from daily object categories. Beyond object category annotations, each salient image is accompanied by attributes that reflect common challenges in real-world scenes. | Provide a detailed description of the following dataset: SOC |
CoSal2015 | Cosal2015 is a large-scale dataset for co-saliency detection which consists of 2,015 images of 50 categories, and each group suffers from various challenging factors such as complex environments, occlusion issues, target appearance variations and background clutters, etc. All these increase the difficulty for accurate ... | Provide a detailed description of the following dataset: CoSal2015 |
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