dataset_name stringlengths 2 128 | description stringlengths 1 9.7k | prompt stringlengths 59 185 |
|---|---|---|
DR-VCTK | This dataset is a new variant of the voice cloning toolkit (VCTK) dataset: device-recorded VCTK (DR-VCTK), where the high-quality speech signals recorded in a semi-anechoic chamber using professional audio devices are played back and re-recorded in office environments using relatively inexpensive consumer devices. | Provide a detailed description of the following dataset: DR-VCTK |
IoT Inspector | **IoT Inspector** is a large dataset of labeled network traffic from smart home devices from within real-world home networks. It is used to conduct data-driven smart home research. An open source tool with the same name has been used to collect data from 44,956 smart home devices across 13 categories and 53 vendors. | Provide a detailed description of the following dataset: IoT Inspector |
BugSwarm | **BugSwarm** is a dataset of reproducible faults and fixes to perform experimental evaluation of approaches to software quality. The BugSwarm toolkit has already gathered 3,091 fail-pass pairs, in Java and Python, all packaged within fully reproducible containers. | Provide a detailed description of the following dataset: BugSwarm |
Peer to Peer Hate | **Peer to Peer Hate** is a comprehensive hate speech dataset capturing various types of hate. It has been built from 27,330 hate speech tweets. | Provide a detailed description of the following dataset: Peer to Peer Hate |
Dense Forest Trail | **Dense Forest Trail** is an UAV dataset collected from a variety of simulated environment in Unreal Engine. | Provide a detailed description of the following dataset: Dense Forest Trail |
MengeROS | MengeROS is an open-source crowd simulation tool for robot navigation that integrates Menge with ROS. It extends Menge to introduce one or more robot agents into a crowd of pedestrians. Each robot agent is controlled by external ROS-compatible controllers. MengeROS has been used to simulate crowds with up to 1000 pedes... | Provide a detailed description of the following dataset: MengeROS |
Dizi | **Dizi** is a dataset of music style of the Northern school and the Southern School. Characteristics include melody and playing techniques of the two different music styles are deconstructed. | Provide a detailed description of the following dataset: Dizi |
P3 | A set of patterns used in psychophysical research to evaluate the ability of saliency algorithms to find targets distinct from distractors in orientation, color and size. Each image is a 7x7 grid and contains a single target. All images are 1024x1024px and have corresponding ground truth masks for the target and distra... | Provide a detailed description of the following dataset: P3 |
O3 | A set of realistic odd-one-out stimuli gathered "in the wild". Each image in the Odd-One-Out (O3) dataset depicts a scene with multiple objects similar to each other in appearance (distractors) and a singleton (target) distinct in one or more feature dimensions (e.g. color, shape, size). All images are resized so that ... | Provide a detailed description of the following dataset: O3 |
KvasirCapsule-SEG | The dataset contains a Video capsule endoscopy dataset for polyp segmentation.
The dataset can be downloaded from here:
https://www.kaggle.com/debeshjha1/kvasircapsuleseg
https://www.dropbox.com/home/KvasirCapsule-SEG
The detail about the dataset can be found from
https://arxiv.org/pdf/2104.11138.pdf | Provide a detailed description of the following dataset: KvasirCapsule-SEG |
Kvasir-Sessile dataset | The Kvasir-SEG dataset includes 196 polyps smaller than 10 mm classified as Paris class 1 sessile or Paris class IIa. We have selected it with the help of expert gastroenterologists. We have released this dataset separately as a subset of Kvasir-SEG. We call this subset Kvasir-Sessile.
The dataset is publicly avai... | Provide a detailed description of the following dataset: Kvasir-Sessile dataset |
Kvasir-Capsule | Kvasir-Capsule dataset is the largest publicly released VCE dataset. In total, the dataset contains 47,238 labeled images and 117 videos, where it captures anatomical landmarks and pathological and normal findings. The results is more than 4,741,621 images and video frames altogether. | Provide a detailed description of the following dataset: Kvasir-Capsule |
Hyper-Kvasir Dataset | HyperKvasir dataset contains 110,079 images and 374 videos where it captures anatomical landmarks and pathological and normal findings. A total of around 1 million images and video frames altogether. | Provide a detailed description of the following dataset: Hyper-Kvasir Dataset |
pathbased | **pathbased** is a 3-cluster data set. The data set consists of a circular cluster with an opening near the bottom and two Gaussian distributed clusters inside. Each cluster contains 100 data points. | Provide a detailed description of the following dataset: pathbased |
Gun Detection Dataset | This is a gun detection dataset with 51K annotated gun images for gun detection and other 51K cropped gun chip images for gun classification collected from a few different sources. | Provide a detailed description of the following dataset: Gun Detection Dataset |
RADDet | **RADDet** is a radar dataset that contains radar data in the form of Range-Azimuth-Doppler tensors along with the bounding boxes on the tensor for dynamic road users, category labels, and 2D bounding boxes on the Cartesian Bird-Eye-View range map. It is used to train and evaluate methods for object detection using aut... | Provide a detailed description of the following dataset: RADDet |
RoadAnomaly21 | **RoadAnomaly21** is a dataset for anomaly segmentation, the task of identify the image regions containing objects that have never been seen during training. It consists of an evaluation dataset of 100 images with pixel-level annotations. Each image contains at least one anomalous object, e.g. animals or unknown vehicl... | Provide a detailed description of the following dataset: RoadAnomaly21 |
MARS Map | **MARS Map** is a set of three dataset collected to evaluate the performance of mapping algorithms within a room and between rooms. | Provide a detailed description of the following dataset: MARS Map |
FFT-75 | The **FFT-75** dataset contains randomly sampled, potentially overlapping file fragments from 75 popular file types. It is a diverse and balanced dataset which is labeled with class IDs and is ready for training supervised machine learning models. We distinguish 6 different scenarios with different granularity and prov... | Provide a detailed description of the following dataset: FFT-75 |
Windows PE Malware | This is a dataset for the task of PE-type malware in the Windows operating system. The different samples in the dataset are classified into 8 main malware families: Trojan, Backdoor, Downloader, Worms, Spyware Adware, Dropper, Virus. | Provide a detailed description of the following dataset: Windows PE Malware |
Bonn RGB-D Dynamic | **Bonn RGB-D Dynamic** is a dataset for RGB-D SLAM, containing highly dynamic sequences. We provide 24 dynamic sequences, where people perform different tasks, such as manipulating boxes or playing with balloons, plus 2 static sequences. For each scene we provide the ground truth pose of the sensor, recorded with an Op... | Provide a detailed description of the following dataset: Bonn RGB-D Dynamic |
VMRD | **VMRD** is a multi-object grasp dataset. It has been collected and labeled using hundreds of objects coming from 31 categories. There are totally 5,185 images including 17,688 object instances and 51,530 manipulation relationships. | Provide a detailed description of the following dataset: VMRD |
TSP/HCP Benchmark set | This is a benchmark set for Traveling salesman problem (TSP) with characteristics that are different from the existing benchmark sets. In particular, it focuses on small instances which prove to be challenging for one or more state-of-the-art TSP algorithms. These instances are based on difficult instances of Hamiltoni... | Provide a detailed description of the following dataset: TSP/HCP Benchmark set |
Logic Bombs | This is a set of small programs with logic bombs. The logic bomb can be triggered when certain conditions are met. Any dynamic testing tools (especially symbolic execution) can employ the dataset to benchmark their capabilities. | Provide a detailed description of the following dataset: Logic Bombs |
CapriDB | **CapriDB** is a 3D object database for robotics. | Provide a detailed description of the following dataset: CapriDB |
Xamarin Q&A | **Xamarin Q&A** consists of two datasets of questions and answers for studying the development of cross-platform mobile applications using the Xamarin framework. The two datasets were created by mining two Q&A sites: Xamarin Forum and Stack Overflow. The datasets have 85,908 questions mined from the Xamarin Forum and 4... | Provide a detailed description of the following dataset: Xamarin Q&A |
3DSSG | 3DSSG provides 3D semantic scene graphs for 3RScan. A semantic scene graph is defined by a set of tuples between nodes and edges where nodes represent specific 3D object instances in a 3D scan. Nodes are defined by its semantics, a hierarchy of classes as well as a set of attributes that describe the visual and physica... | Provide a detailed description of the following dataset: 3DSSG |
AudioCaps | **AudioCaps** is a dataset of sounds with event descriptions that was introduced for the task of audio captioning, with sounds sourced from the [AudioSet](https://paperswithcode.com/dataset/audioset) dataset. Annotators were provided the audio tracks together with category hints (and with additional video hints if need... | Provide a detailed description of the following dataset: AudioCaps |
ToolNet | The dataset is organized as follows. We have 8 different goals and 10 different world instances for both the domains, home and factory. Each domain has 8 directories corresponding to the goals possible for the domain. These goals itself, contain directories for the 10 different world instances. Each goal for each world... | Provide a detailed description of the following dataset: ToolNet |
CollATe | The **CollATe** dataset is large dataset consisting of two types of collusive entities on YouTube – videos submitted to gain collusive likes and comment requests, and channels submitted to gain collusive subscriptions. | Provide a detailed description of the following dataset: CollATe |
Semantic Trails | Semantic Trails Datasets (STDs) are two different datasets of semantically annotated trails created starting from check-ins performed on the Foursquare social network. | Provide a detailed description of the following dataset: Semantic Trails |
360 EM | Data set of 360-degree equirectangular videos, gaze recordings, eye movement (EM) ground-truth and an automatic EM classification algorithm. | Provide a detailed description of the following dataset: 360 EM |
Innovation and Revenue | This is a dataset that catalogs 2.6 million patents granted between 2005 and 2017. | Provide a detailed description of the following dataset: Innovation and Revenue |
Pull Request Descriptions | This is a dataset of over 333K Pull Requests, used for automatic pull request description generation. | Provide a detailed description of the following dataset: Pull Request Descriptions |
Reddit Norm Violations | This is a dataset of over 40K Reddit comments removed by moderators according to the specific type of macro norm being violated. | Provide a detailed description of the following dataset: Reddit Norm Violations |
DBLP Temporal | **DBLP Temporal** is a dataset for temporal entity resolution, based on author profiles extracted from the Digital Bibliography and Library Project (DBLP). | Provide a detailed description of the following dataset: DBLP Temporal |
Rediscovery Datasets | We present three defect rediscovery datasets mined from Bugzilla. The datasets capture data for three groups of open source software projects: Apache, Eclipse, and KDE. The datasets contain information about approximately 914 thousands of defect reports over a period of 18 years (1999-2017) to capture the inter-relatio... | Provide a detailed description of the following dataset: Rediscovery Datasets |
FLOBOT Perception | This dataset was collected with FLOBOT - an advanced autonomous floor scrubber - includes data from four different sensors for environment perception, as well as the robot pose in the world reference frame. Specifically, FLOBOT relies on a 3D lidar and a RGB-D camera for human detection and tracking, and a second RGB-D... | Provide a detailed description of the following dataset: FLOBOT Perception |
Collision Avoidance Challenge dataset | The Collision Avoidance Challenge dataset is the official dataset used during the **ESA's Kelvins competition for "Collision Avoidance Challenge"**. The dataset is a collection of Conjunction Data Messages (CDMs) received by ESA from 2015 to 2019. The CDMs have been anonymised for distribution. The initial raw data, as... | Provide a detailed description of the following dataset: Collision Avoidance Challenge dataset |
OREBA | The OREBA dataset aims to provide a comprehensive multi-sensor recording of communal intake occasions for researchers interested in automatic detection of intake gestures. Two scenarios are included, with 100 participants for a discrete dish and 102 participants for a shared dish, totalling 9069 intake gestures. Availa... | Provide a detailed description of the following dataset: OREBA |
IWSLT2015 | The IWSLT 2015 Evaluation Campaign featured three tracks: automatic speech recognition (ASR), spoken language translation (SLT), and machine translation (MT). For ASR we offered two tasks, on English and German, while
for SLT and MT a number of tasks were proposed, involving English, German, French, Chinese, Czech, Th... | Provide a detailed description of the following dataset: IWSLT2015 |
MIMII DUE | This dataset is a sound dataset for malfunctioning industrial machine investigation and inspection with domain shifts due to changes in operational and environmental conditions (MIMII DUE). The dataset consists of normal and abnormal operating sounds of five different types of industrial machines, i.e., fans, gearboxes... | Provide a detailed description of the following dataset: MIMII DUE |
DroneCrowd | **DroneCrowd** is a benchmark for object detection, tracking and counting algorithms in drone-captured videos. It is a drone-captured large scale dataset formed by 112 video clips with 33,600 HD frames in various scenarios. Notably, it has annotations for 20,800 people trajectories with 4.8 million heads and several vi... | Provide a detailed description of the following dataset: DroneCrowd |
Content4All | **Content4All** is a collection of six open research datasets aimed at automatic sign language translation research.
Sign language interpretation footage was captured by the broadcast partners SWISSTXT and VRT. Raw footage was anonymized and processed to extract 2D and 3D human
body pose information. From the rough... | Provide a detailed description of the following dataset: Content4All |
MIAP | **MIAP** is a dataset created by obtaining a new set of annotations on a subset of the [Open Images](/dataset/open-images-v4) dataset, containing bounding boxes and attributes for all of the people visible in those images, as the original Open Images dataset annotations are not exhaustive, with bounding boxes and attri... | Provide a detailed description of the following dataset: MIAP |
MQTT-IoT-IDS2020 | Message Queuing Telemetry Transport (MQTT) protocol is one of the most used standards used in Internet of Things (IoT) machine to machine communication. The increase in the number of available IoT devices and used protocols reinforce the need for new and robust Intrusion Detection Systems (IDS). However, building IoT I... | Provide a detailed description of the following dataset: MQTT-IoT-IDS2020 |
Backstabber’s Knife Collection | Backstabber’s Knife Collection is a dataset of 174 malicious software packages that were used in real-world attacks on open source software supply chains, and which were distributed via the popular package repositories npm, PyPI, and RubyGems. Those packages, dating from November 2015 to November 2019, were manually co... | Provide a detailed description of the following dataset: Backstabber’s Knife Collection |
Ukiyo-e Faces | The ukiyo-e faces dataset comprises of 5209 images of faces from ukiyo-e prints. The images are 1024x1024 pixels in jpeg format and have been aligned using the procedure used for the FFHQ dataset | Provide a detailed description of the following dataset: Ukiyo-e Faces |
Data Loss repository | This is a benchmark of data loss bugs for android apps. It is a public benchmark of 110 data loss faults in Android apps that we systematically collected to facilitate research and experimentation with these problems. The benchmark is available on GitLab and includes the faulty apps, the fixed apps (when available), th... | Provide a detailed description of the following dataset: Data Loss repository |
RePack | **RePack** is a dataset to study the detection of repackaged Android apps. | Provide a detailed description of the following dataset: RePack |
PFN-VT | **PFN-VT** is a dataset for the estimation of tactile properties from vision, such as slipperiness or roughness. The dataset is collected with a webcam and uSkin tactile sensor mounted on the end-effector of a Sawyer robot, which strokes the surfaces of 25 different materials. | Provide a detailed description of the following dataset: PFN-VT |
Twitter Abusive Behavior | 80k tweets annotated concerning Inappropriate Speech (more particularly in matters of Abusive and Hateful speech) as well as Normal and Spam. | Provide a detailed description of the following dataset: Twitter Abusive Behavior |
CinemAirSim | **CinemAirSim** is an extension of the well-known drone simulator, [AirSim](airsim), with a cinematic camera as well as extended its API to control all of its parameters in real time, including various filming lenses and common cinematographic properties. | Provide a detailed description of the following dataset: CinemAirSim |
ICDCN2019 | This is a dataset consisting of complete network traces comprising benign and malicious traffic, which is feature-rich and publicly available. | Provide a detailed description of the following dataset: ICDCN2019 |
Mal-Activity | This is a dataset of Internet malicious activity (mal-activity in short). It contains more than 51 million mal-activity reports involving 662K unique IP addresses covering the period form January 2007 to June 2017. Leveraging the Wayback Machine, antivirus (AV) tool reports and several additional public datasets (e.g.,... | Provide a detailed description of the following dataset: Mal-Activity |
α-Satellite | This is a collection of datasets related to Covid-19. It consists of large scale and real-time pandemic related data from multiple sources, including disease related data from official public health organizations and digital media, demographic data, mobility data, and user generated data from social media (i.e., Reddit... | Provide a detailed description of the following dataset: α-Satellite |
VAST Absorption | **VAST Absorption** is a dataset of spatial binaural features annotated with acoustic properties such as the 3D source position and the walls’ absorption coefficients. | Provide a detailed description of the following dataset: VAST Absorption |
On the Origins of Memes by Means of Fringe Web Communities | This dataset was collected with research funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No 691025.
The dataset consists of all the URLs and phashes for images from Twitter, Reddit, 4chan's /pol/, and Gab posted between July 2016 and e... | Provide a detailed description of the following dataset: On the Origins of Memes by Means of Fringe Web Communities |
Bimanual Actions Dataset | The Bimanual Actions Dataset is a collection of 540 RGB-D videos, showing subjects perform bimanual actions in a kitchen or workshop context. The main purpose for its compilation is to research bimanual human behaviour in order to eventually improve the capabilities of humanoid robots. | Provide a detailed description of the following dataset: Bimanual Actions Dataset |
ColosseumRL | **ColosseumRL** is a framework for research in reinforcement learning in n-player games.
ColosseumRL contains a number of multiagent free-for-all games. Currently, we have Tron, Blokus, and 3 and 4-player tic-tac-toe. In the future, we will be adding Chinese checkers and other similar games. Tron is a fully-observab... | Provide a detailed description of the following dataset: ColosseumRL |
Online Cryptocurrency-topic diffusion on Twitter, Telegram, and Discord | This Dataset is described in Charting the Landscape of Online Cryptocurrency Manipulation. IEEE Access (2020), a study that aims to map and assess the extent of cryptocurrency manipulations within and across the online ecosystems of Twitter, Telegram, and Discord. Starting from tweets mentioning cryptocurrencies, we le... | Provide a detailed description of the following dataset: Online Cryptocurrency-topic diffusion on Twitter, Telegram, and Discord |
3D-Printing-Data | This is a dataset for anomalies detection in 3D printing. | Provide a detailed description of the following dataset: 3D-Printing-Data |
Grasp Affordance | This is a dataset for visual grasp affordance prediction that promotes more robust and heterogeneous robotic grasping methods. The dataset contains different attributes from 30 different objects. Each object instance is related not only to the semantic descriptions, but also the physical features describing visual attr... | Provide a detailed description of the following dataset: Grasp Affordance |
DeformingThings4D | **DeformingThings4D** is a synthetic dataset containing 1,972 animation sequences spanning 31 categories of humanoids and animals. It provides 200 animations for humanoids and 1772 animations for animals.
#### Use case of the dataset
The dataset is designed to tackle the following tasks using data-driven approac... | Provide a detailed description of the following dataset: DeformingThings4D |
Visual Servoing | Dataset for visual servoing (VS) and camera pose estimation.
The images were obtained by a manipulator robot with an eye-in-hand camera in different poses.
The labels represent the camera pose.
It is possible to obtain the absolute pose of the camera without any pre-processing of the dataset, as well as the relat... | Provide a detailed description of the following dataset: Visual Servoing |
DeepStab | **DeepStab** is a dataset for online video stabilization consisting of synchronized steady/unsteady video pairs collected via a well designed hand-held hardware. | Provide a detailed description of the following dataset: DeepStab |
CxC | Crisscrossed Captions (CxC) contains 247,315 human-labeled annotations including positive and negative associations between image pairs, caption pairs and image-caption pairs.
Image source: [Crisscrossed Captions: Extended Intramodal and Intermodal Semantic Similarity Judgments for MS-COCO](https://arxiv.org/pdf/200... | Provide a detailed description of the following dataset: CxC |
AdversarialQA | We have created three new Reading Comprehension datasets constructed using an adversarial model-in-the-loop.
We use three different models; BiDAF (Seo et al., 2016), BERTLarge (Devlin et al., 2018), and RoBERTaLarge (Liu et al., 2019) in the annotation loop and construct three datasets; D(BiDAF), D(BERT), and D(RoBE... | Provide a detailed description of the following dataset: AdversarialQA |
3DCSR dataset | Cross-source point cloud dataset for registration task. It includes point clouds from structure from motion (SFM), Kinect, Lidar. | Provide a detailed description of the following dataset: 3DCSR dataset |
DTU | DTU MVS 2014 is a multi-view stereo dataset, which is an order of magnitude larger in number of scenes and with a significant increase in diversity. Specifically, it contains 80 scenes of large variability. Each scene consists of 49 or 64 accurate camera positions and reference structured light scans, all acquired by a... | Provide a detailed description of the following dataset: DTU |
Tanks and Temples | We present a benchmark for image-based 3D reconstruction. The benchmark sequences were acquired outside the lab, in realistic conditions. Ground-truth data was captured using an industrial laser scanner. The benchmark includes both outdoor scenes and indoor environments. High-resolution video sequences are provided as ... | Provide a detailed description of the following dataset: Tanks and Temples |
IAPR TC-12 | The image collection of the IAPR TC-12 Benchmark consists of 20,000 still natural images taken from locations around the world and comprising an assorted cross-section of still natural images. This includes pictures of different sports and actions, photographs of people, animals, cities, landscapes, and many other aspe... | Provide a detailed description of the following dataset: IAPR TC-12 |
QASPER | **QASPER** is a dataset for question answering on scientific research papers. It consists of 5,049 questions over 1,585 Natural Language Processing papers. Each question is written by an NLP practitioner who read only the title and abstract of the corresponding paper, and the question seeks information present in the f... | Provide a detailed description of the following dataset: QASPER |
im2latex-100k | A prebuilt dataset for OpenAI's task for image-2-latex system. Includes total of ~100k formulas and images splitted into train, validation and test sets. Formulas were parsed from LaTeX sources provided here: http://www.cs.cornell.edu/projects/kddcup/datasets.html(originally from arXiv)
Each image is a PNG image of... | Provide a detailed description of the following dataset: im2latex-100k |
RLBench | **RLBench** is an ambitious large-scale benchmark and learning environment designed to facilitate research in a number of vision-guided manipulation research areas, including: reinforcement learning, imitation learning, multi-task learning, geometric computer vision, and in particular, few-shot learning. | Provide a detailed description of the following dataset: RLBench |
MULTEXT-East | The **MULTEXT-East** resources are a multilingual dataset for language engineering research and development. It consists of the (1) MULTEXT-East morphosyntactic specifications, defining categories (parts-of-speech), their morphosyntactic features (attributes and values), and the compact MSD tagset representations; (2) ... | Provide a detailed description of the following dataset: MULTEXT-East |
SketchyCOCO | SketchyCOCO dataset consists of two parts:
**Object-level data**
Object-level data contains $20198(train18869+val1329)$ triplets of {foreground sketch, foreground image, foreground edge map} examples covering 14 classes, $27683(train22171+val5512)$ pairs of {background sketch, background image} examples covering ... | Provide a detailed description of the following dataset: SketchyCOCO |
Scribble | **Scribble** is a new outline dataset consisting of 200 images (150 train, 50 test) for each of 10 classes – basketball, chicken, cookie, cupcake, moon, orange, soccer, strawberry, watermelon and pineapple. All the images have a white background and were collected using search keywords on popular search engines. In eac... | Provide a detailed description of the following dataset: Scribble |
Milling Data Set | Experiments on a metal milling machine for different speeds, feeds, and depth of cut. Records the wear of the milling insert, VB. The data set was provided by the BEST lab at UC Berkeley. | Provide a detailed description of the following dataset: Milling Data Set |
Wiki-Reliability | Wiki-Reliability is the first dataset of English Wikipedia articles annotated with a wide set of content reliability issues. Templates are tags used by expert Wikipedia editors to indicate content issues, such as the presence of "non-neutral point of view" or "contradictory articles", and serve as a strong signal for d... | Provide a detailed description of the following dataset: Wiki-Reliability |
ExpMRC | **ExpMRC** is a benchmark for the Explainability evaluation of Machine Reading Comprehension. ExpMRC contains four subsets of popular MRC datasets with additionally annotated evidences, including [SQuAD](squad), [CMRC 2018](cmrc-2018), RACE+ (similar to [RACE](race)), and [C3](c3), covering span-extraction and multiple... | Provide a detailed description of the following dataset: ExpMRC |
DiagSet | **DiagSet** is a histopathological dataset for prostate cancer detection. The proposed dataset consists of over 2.6 million tissue patches extracted from 430 fully annotated scans, 4675 scans with assigned binary diagnosis, and 46 scans with diagnosis given independently by a group of histopathologists. | Provide a detailed description of the following dataset: DiagSet |
gComm | **gComm** is a step towards developing a robust platform to foster research in grounded language acquisition in a more challenging and realistic setting. It comprises a 2-D grid environment with a set of agents (a stationary speaker and a mobile listener connected via a communication channel) exposed to a continuous ar... | Provide a detailed description of the following dataset: gComm |
e-ViL | **e-ViL** is a benchmark for explainable vision-language tasks. e-ViL spans across three datasets of human-written NLEs (natural language explanations), and provides a unified evaluation framework that is designed to be re-usable for future works.
This benchmark uses the following datasets: [e-SNLI-VE](e-snli-ve), [... | Provide a detailed description of the following dataset: e-ViL |
e-SNLI-VE | e-SNLI-VE is a large VL (vision-language) dataset with NLEs (natural language explanations) with over 430k instances for which the explanations rely on the image content. It has been built by merging the explanations from [e-SNLI](e-snli) and the image-sentence pairs from [SNLI-VE](snli-ve). | Provide a detailed description of the following dataset: e-SNLI-VE |
HLGD | The Headline Grouping dataset is a binary classification dataset on pairs of news headline.
For each pair of headline, the binary label indicates whether the two headlines are part of the same group (and describe the same underlying event), or whether they are in distinct groups.
The dataset contains a total of 20k a... | Provide a detailed description of the following dataset: HLGD |
CRUW | **CRUW** is a dataset for the radar object detection (ROD) task, which aims to classify and localize the objects in 3D purely from radar's radio frequency (RF) images. The CRUW dataset has a systematic annotation and evaluation system, which involves camera RGB images and radar RF images, collected in various driving s... | Provide a detailed description of the following dataset: CRUW |
FoodSeg103 | **FoodSeg103** is a new food image dataset containing 7,118 images. Images are annotated with 104 ingredient classes and each image has an average of 6 ingredient labels and pixel-wise masks. It's provided as a large-scale benchmark for food image segmentation.
Major Challenges:
1. High intra-variance of the same... | Provide a detailed description of the following dataset: FoodSeg103 |
Kleister NDA | **Kleister NDA** is a dataset for Key Information Extraction (KIE). The dataset contains a mix of scanned and born-digital long formal English-language documents. For this datasets, an NLP system is expected to find or infer various types of entities by employing both textual and structural layout features. The Kleist... | Provide a detailed description of the following dataset: Kleister NDA |
LabPics | LabPics Chemistry Dataset
Dataset for computer vision for materials segmentation and classification in chemistry labs, medical labs, and any setting where materials are handled inside containers.
The Vector-LabPics dataset comprises 7900 images of materials in various phases and processes within mostly transparent ... | Provide a detailed description of the following dataset: LabPics |
TextOCR | **TextOCR** is a dataset to benchmark text recognition on arbitrary shaped scene-text. TextOCR requires models to perform text-recognition on arbitrary shaped scene-text present on natural images. TextOCR provides ~1M high quality word annotations on TextVQA images allowing application of end-to-end reasoning on downst... | Provide a detailed description of the following dataset: TextOCR |
Scientific statement classification dataset from arXMLiv 08.2018 | This resource contains 10.5 million paragraphs with associated statement labels, realized as one paragraph per file, one sentence per line. Each file is placed in a subdirectory named after its annotated class. The statements were extracted from author-annotated environments, where we only selected the first paragraph,... | Provide a detailed description of the following dataset: Scientific statement classification dataset from arXMLiv 08.2018 |
arXMLiv:08.2018 | This is a second public release of the arXMLiv dataset generated by the KWARC research group. It contains 1,232,186 HTML5 scientific documents from the arXiv.org preprint archive, converted from their respective TeX sources. A 13% increase in available articles over the 08.2017 release.
The dataset is segmented in 3... | Provide a detailed description of the following dataset: arXMLiv:08.2018 |
Extreme Countix-AV | * 214 videos under various extreme sight conditions for audiovisual repetition counting
* 7 vision challenges: camera viewpoint changes, cluttered background, low illumination, fast motion, disappearing activity, scale variation, low resolution | Provide a detailed description of the following dataset: Extreme Countix-AV |
Ninapro DB5 | The 5th Ninapro database includes 10 intact subjects recorded with two Thalmic Myo (https://www.myo.com/) armbands.
The database can be used to test the Myo armbands separately as well.
The 5th Ninapro database is thoroughly described in the paper: ["Stefano Pizzolato, Luca Tagliapietra, Matteo Cognolato, Monica Regg... | Provide a detailed description of the following dataset: Ninapro DB5 |
Copel-AMR | This dataset contains 12,500 meter images acquired in the field by the employees of the Energy Company of Paraná (Copel), which directly serves more than 4 million consuming units, across 395 cities and 1,113 locations (i.e., districts, villages and settlements), located in the Brazilian state of Paraná.
Copel-AMR i... | Provide a detailed description of the following dataset: Copel-AMR |
BRUSH | The BRUSH dataset (BRown University Stylus Handwriting) contains 27,649 online handwriting samples from a total of 170 writers. Every sequence is labeled with intended characters such that dataset users can identify to which character a point in a sequence corresponds. The dataset was introduced in the paper "Generatin... | Provide a detailed description of the following dataset: BRUSH |
UFPR-ALPR | This dataset includes 4,500 fully annotated images (over 30,000 license plate characters) from 150 vehicles in real-world scenarios where both the vehicle and the camera (inside another vehicle) are moving.
The images were acquired with three different cameras and are available in the Portable Network Graphics (PNG)... | Provide a detailed description of the following dataset: UFPR-ALPR |
SSIG-SegPlate | This dataset aims at evaluating the License Plate Character Segmentation (LPCS) problem. The experimental results of the paper Benchmark for License Plate Character Segmentation were obtained using a dataset providing 101 on-track vehicles captured during the day. The video was recorded using a static camera in early 2... | Provide a detailed description of the following dataset: SSIG-SegPlate |
Caltech Cars | The Caltech Cars dataset consists of 126 rear-view photographs captured within parking lots. These images possess a resolution of 896 × 592 pixels, featuring a solitary vehicle as the primary subject. The acquisitions were made during daylight hours employing a handheld camera at roughly equivalent distances for all in... | Provide a detailed description of the following dataset: Caltech Cars |
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