dataset_name stringlengths 2 128 | description stringlengths 1 9.7k | prompt stringlengths 59 185 |
|---|---|---|
ASR-ETeleCSC: An English Telephone Conversational Speech Corpus | This open-source dataset consists of 5.04 hours of transcribed English conversational speech beyond telephony, where 13 conversations were contained. | Provide a detailed description of the following dataset: ASR-ETeleCSC: An English Telephone Conversational Speech Corpus |
CaFFe | The temporal variability in calving front positions of marine-terminating glaciers permits inference on the frontal ablation. Frontal ablation, the sum of the calving rate and the melt rate at the terminus, significantly contributes to the mass balance of glaciers. Therefore, the glacier area has been declared as an Es... | Provide a detailed description of the following dataset: CaFFe |
CQ500 | Non-contrast head/brain CT of patients with head trauma or stroke symptoms. | Provide a detailed description of the following dataset: CQ500 |
ASR-RAMC-BIGCCSC: A CHINESE CONVERSATIONAL SPEECH CORPUS | A Rich Annotated Mandarin Conversational (RAMC) Speech Dataset, including 180 hours of Mandarin Chinese dialogue, 150, 10 and 20 hours for the training set, development set and test set respectively.
It contains 351 multi-turn dialogues, each of which is a coherent and compact conversation centered around one theme.
... | Provide a detailed description of the following dataset: ASR-RAMC-BIGCCSC: A CHINESE CONVERSATIONAL SPEECH CORPUS |
Poisoned Water Detection using Smartphone embedded WiFi CSI data and Machine Learning Algorithms | This repository contains a dataset and machine learning algorithms to detect poisoned water from clean water via using equivalent Smartphone embedded Wi-Fi CSI data.
The machine learning algorithm (including k-NN, SVM, LSTM, and Ensemble) are written in MATLAB code!
The testbed is shown in img/p1.jpg
The equiv... | Provide a detailed description of the following dataset: Poisoned Water Detection using Smartphone embedded WiFi CSI data and Machine Learning Algorithms |
FS-Mol | A Few-Shot Learning Dataset of Molecules. | Provide a detailed description of the following dataset: FS-Mol |
YouTube Driving | YouTube Driving Dataset contains a massive amount of real-world driving frames with various conditions, from different weather, different regions, to diverse scene types | Provide a detailed description of the following dataset: YouTube Driving |
CCTSDB2021 | Traffic signs are one of the most important information that guide cars to travel, and the detection of traffic signs is an important component of autonomous driving and intelligent transportation systems. Constructing a traffic sign dataset with many samples and sufficient attribute categories will promote the develop... | Provide a detailed description of the following dataset: CCTSDB2021 |
PACE 2022 Exact | This is the set of graphs used in the [PACE 2022 challenge](https://pacechallenge.org/2022/) for computing the [Directed Feedback Vertex Set](https://en.wikipedia.org/wiki/Feedback_vertex_set), from the Exact track. It consists of 200 labelled directed graphs. The graphs range in size up to from N=512 up to N=131072 ve... | Provide a detailed description of the following dataset: PACE 2022 Exact |
PACE 2022 Heuristic | This is the set of graphs used in the [PACE 2022 challenge](https://pacechallenge.org/2022/) for computing the [Directed Feedback Vertex Set](https://en.wikipedia.org/wiki/Feedback_vertex_set), from the Heuristic track. It consists of 200 labelled directed graphs. The graphs are mostly not symmetric (an edge form u->v ... | Provide a detailed description of the following dataset: PACE 2022 Heuristic |
DigestPath | Introduced by Da et al. in [DigestPath: a Benchmark Dataset with Challenge Review for the Pathological Detection and Segmentation of Digestive-System](https://github.com/bupt-ai-cz/CAC-UNet-DigestPath2019/blob/main/papers/DigestPath-a-Benchmark-Dataset-with-Challenge-Review.pdf)
### [Grand-Challenge Page](https://di... | Provide a detailed description of the following dataset: DigestPath |
AfriSenti | AfriSenti is the largest sentiment analysis dataset for under-represented African languages, covering 110,000+ annotated tweets in 14 African languages (Amharic, Algerian Arabic, Hausa, Igbo, Kinyarwanda, Moroccan Arabic, Mozambican Portuguese, Nigerian Pidgin, Oromo, Swahili, Tigrinya, Twi, Xitsonga, and Yoruba). | Provide a detailed description of the following dataset: AfriSenti |
Jet Flavor dataset | Dataset for 'Jet Flavor Classification in High-Energy Physics with Deep Neural Networks' | Provide a detailed description of the following dataset: Jet Flavor dataset |
SPAVE-28G on NSF POWDER | This paper details the design of an autonomous alignment and tracking platform to mechanically steer directional horn antennas in a sliding correlator channel sounder setup for 28 GHz V2X propagation modeling. A pan-and-tilt subsystem facilitates uninhibited rotational mobility along the yaw and pitch axes, driven by o... | Provide a detailed description of the following dataset: SPAVE-28G on NSF POWDER |
GSV-Cities | GSV-Cities is a large-scale dataset for training deep neural network for the task of Visual Place Recognition.
The dataset contains more than **530k** images:
* There are more than **62k** different places, spread across multiple cities around the globe.
* Each place is depited by at least 4 images (up to 20 ima... | Provide a detailed description of the following dataset: GSV-Cities |
A collection of 131 CT datasets of pieces of modeling clay containing stones | This dataset contains a collection of 131 X-ray CT scans of pieces of modeling clay (Play-Doh) with various numbers of stones inserted, retrieved in the FleX-ray lab at CWI. The dataset consists of 5 parts. It is intended as raw supplementary material to reproduce the CT reconstructions and subsequent results in the pa... | Provide a detailed description of the following dataset: A collection of 131 CT datasets of pieces of modeling clay containing stones |
A collection of X-ray projections of 131 pieces of modeling clay containing stones for machine learning-driven object detection | This dataset contains a collection of 235800 X-ray projections of 131 pieces of modeling clay (Play-Doh) with various numbers of stones inserted. The dataset is intended as an extensive and easy-to-use training dataset for supervised machine learning driven object detection. The ground truth locations of the stones are... | Provide a detailed description of the following dataset: A collection of X-ray projections of 131 pieces of modeling clay containing stones for machine learning-driven object detection |
DIVOTrack | **DIVOTrack** is a cross-view multi-object tracking dataset for DIVerse Open scenes with dense tracking pedestrians in realistic and non-experimental environments. DIVOTrack has ten distinct scenarios and 550 cross-view tracks. | Provide a detailed description of the following dataset: DIVOTrack |
TT100K | Trainging and testing data: The original training set includes 6105 images, and the original testing set includes 3071 images.
Description: Although promising results have been achieved in the areas of traffic-sign detection and classification, few works have provided simultaneous solutions to these two tasks for re... | Provide a detailed description of the following dataset: TT100K |
jazznet | **jazznet** is a dataset of piano patterns for music audio machine learning research. The dataset comprises chords, arpeggios, scales, and chord progressions in all keys of an 88-key piano and in all the inversions, for a total of 162520 labeled piano patterns, resulting in 95GB of data and more than 26k hours of audio... | Provide a detailed description of the following dataset: jazznet |
MO-Gymnasium | MO-Gymnasium is an open source Python library for developing and comparing multi-objective reinforcement learning algorithms by providing a standard API to communicate between learning algorithms and environments, as well as a standard set of environments compliant with that API. Essentially, the environments follow th... | Provide a detailed description of the following dataset: MO-Gymnasium |
S-VED | The Sacrobosco Visual Elements Dataset (S-VED) is derived from 359 Sphaera editions, centered on the Tractatus de sphaera by Johannes de Sacrobosco (โ1256) and printed between 1472 and 1650. The Sphaera editions were primarily used to teach geocentric astronomy to university students across Europe. Their visual element... | Provide a detailed description of the following dataset: S-VED |
PACE 2018 Steiner Tree | This is the set of instances use in the [PACE 2018 competition](https://pacechallenge.org/2018/), of optimal Steiner Tree computation. The instances are grouped into three tracks of 200 instances each, except for the third track which is only 199 instances. Each instance is an undirected graph.
Track 1 is the "exact... | Provide a detailed description of the following dataset: PACE 2018 Steiner Tree |
PACE 2016 Feedback Vertex Set | This is the dataset used in the [PACE 2016 challenge](https://pacechallenge.org/2016/), Track B, which was computing minimal Feedback Vertex Set. This competition focused on exact solutions, i.e. provably minimal feedback vertex sets (and no heuristic solutions). This should not be confused with the PACE 2022 challenge... | Provide a detailed description of the following dataset: PACE 2016 Feedback Vertex Set |
Lot-insts | LoT-insts contains over 25k classes whose frequencies are naturally long-tail distributed. Its test set from four different subsets: many-, medium-, and few-shot sets, as well as a zero-shot open set. To our best knowledge, this is the first natural language dataset that focuses on this long-tailed and open classificat... | Provide a detailed description of the following dataset: Lot-insts |
Weather2K | A multivariate spatio-temporal benchmark dataset for meteorological forecasting based on real-time observation data from ground weather stations. | Provide a detailed description of the following dataset: Weather2K |
ImageNet C-OOD (class-out-of-distribution) | This dataset was presented as part of the ICLR 2023 paper ๐ ๐ง๐ณ๐ข๐ฎ๐ฆ๐ธ๐ฐ๐ณ๐ฌ ๐ง๐ฐ๐ณ ๐ฃ๐ฆ๐ฏ๐ค๐ฉ๐ฎ๐ข๐ณ๐ฌ๐ช๐ฏ๐จ ๐๐ญ๐ข๐ด๐ด-๐ฐ๐ถ๐ต-๐ฐ๐ง-๐ฅ๐ช๐ด๐ต๐ณ๐ช๐ฃ๐ถ๐ต๐ช๐ฐ๐ฏ ๐ฅ๐ฆ๐ต๐ฆ๐ค๐ต๐ช๐ฐ๐ฏ ๐ข๐ฏ๐ฅ ๐ช๐ต๐ด ๐ข๐ฑ๐ฑ๐ญ๐ช๐ค๐ข๐ต๐ช๐ฐ๐ฏ ๐ต๐ฐ ๐๐ฎ๐ข๐จ๐ฆ๐๐ฆ๐ต.
It is a framework that, based on this dataset (a subset of the ImageNet-21k da... | Provide a detailed description of the following dataset: ImageNet C-OOD (class-out-of-distribution) |
Performance Improving Code Edits (PIE) | **PIE** stands for Performance Improving Code Edits. PIE contains trajectories of programs, where a programmer begins with an initial, slower version and iteratively
makes changes to improve the programโs performance. | Provide a detailed description of the following dataset: Performance Improving Code Edits (PIE) |
OPT | Accurately tracking the six degree-of-freedom pose of an object in real scenes is an important task in computer vision and augmented reality with numerous applications. Although a variety of algorithms for this task have been proposed, it remains difficult to evaluate existing methods in the literature as oftentimes di... | Provide a detailed description of the following dataset: OPT |
VEDAI | VEDAI is a dataset for Vehicle Detection in Aerial Imagery, provided as a tool to benchmark automatic target recognition algorithms in unconstrained environments. The vehicles contained in the database, in addition of being small, exhibit different variabilities such as multiple orientations, lighting/shadowing changes... | Provide a detailed description of the following dataset: VEDAI |
RTB | The Robot Tracking Benchmark (RTB) is a synthetic dataset that facilitates the quantitative evaluation of 3D tracking algorithms for multi-body objects. It was created using the procedural rendering pipeline BlenderProc. The dataset contains photo-realistic sequences with HDRi lighting and physically-based materials. P... | Provide a detailed description of the following dataset: RTB |
NNID | We build what we name the Nearly-Nested Image Datasets (NNID) such that each dataset owns images of the same dimension, and each dataset is issued from a cropped version of the images belonging to the dataset with the biggest dimensions. This last dataset is named mother dataset and the images are named mother images. ... | Provide a detailed description of the following dataset: NNID |
Video Localized Narratives | **Video Localized Narratives** is a new form of multimodal video annotations connecting vision and language. The annotations are created from videos with Localized Narratives, capturing even complex events involving multiple actors interacting with each other and with several passive objects. It contains annotations of... | Provide a detailed description of the following dataset: Video Localized Narratives |
ArtiFact | The ArtiFact dataset is a large-scale image dataset that aims to include a diverse collection of real and synthetic images from multiple categories, including Human/Human Faces, Animal/Animal Faces, Places, Vehicles, Art, and many other real-life objects. The dataset comprises 8 sources that were carefully chosen to en... | Provide a detailed description of the following dataset: ArtiFact |
MVTec LOCO AD | **MVTec Logical Constraints Anomaly Detection (MVTec LOCO AD)** dataset is intended for the evaluation of unsupervised anomaly localization algorithms. The dataset includes both structural and logical anomalies. It contains 3644 images from five different categories inspired by real-world industrial inspection scenario... | Provide a detailed description of the following dataset: MVTec LOCO AD |
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... | Provide a detailed description of the following dataset: VoiceBank+DEMAND |
FetReg: Largescale Multi-centre Fetoscopy Placenta Dataset | Fetoscopic Placental Vessel Segmentation and Registration (FetReg2021) challenge was organized as part of the MICCAI2021 Endoscopic Vision (EndoVis) challenge. Through FetReg2021 challenge, we released the first large-scale multi-centre dataset of fetoscopy laser photocoagulation procedure. The dataset contains 2,718 p... | Provide a detailed description of the following dataset: FetReg: Largescale Multi-centre Fetoscopy Placenta Dataset |
V-PCCD | A simulated dataset built in Unreal Engine 4 with AirSim. Designed for visual point cloud change detection. Including GT point clouds before changes and after changes. Besides, 4 trajectories with stereo camera and IMU data are recorded for change detection task. | Provide a detailed description of the following dataset: V-PCCD |
Press Briefing Claim Dataset | # Press Briefing Claim Dataset
The dataset contains a total of 53 press briefings from a time span of over four years (2017-2021). While, on average, one press briefing per month is held, the distribution is highly skewed towards recent years.
The Press briefings can be categorized into five main thematic categor... | Provide a detailed description of the following dataset: Press Briefing Claim Dataset |
VIS30K | We present the VIS30K dataset, a collection of 29,689 images that represents 30 years of figures and tables from each track
of the IEEE Visualization conference series (Vis, SciVis, InfoVis, VAST). VIS30Kโs comprehensive coverage of the scientific literature in
visualization not only reflects the progress of the fiel... | Provide a detailed description of the following dataset: VIS30K |
UEA time-series datasets | Five datasets used in NeurTraL-AD paper: \textit{RacketSports (RS).} Accelerometer and gyroscope recording of players playing four different racket sports. Each sport is designated as a different class. \textit{Epilepsy (EPSY).} Accelerometer recording of healthy actors simulating four different activity classes, one o... | Provide a detailed description of the following dataset: UEA time-series datasets |
ProofNet | **ProofNet** is a benchmark for autoformalization and formal proving of undergraduate-level mathematics. The ProofNet benchmarks consists of 371 examples, each consisting of a formal theorem statement in Lean 3, a natural language theorem statement, and natural language proof. The problems are primarily drawn from popu... | Provide a detailed description of the following dataset: ProofNet |
CMU Panoptic Dataset 2.0 | The field of biomechanics is at a turning point, with marker-based motion capture set to be replaced by portable and inexpensive hardware, rapidly improving markerless tracking algorithms, and open datasets that will turn these new technologies into field-wide team projects. To expedite progress in this direction, we h... | Provide a detailed description of the following dataset: CMU Panoptic Dataset 2.0 |
Dubbing Test Set | **Dubbing Test Set** consists of two subsets extracted from the EnโDe test set of COVOST-2, a large-scale multilingual speech translation corpus based on Common Voice. Specifically, the first subset is created by randomly sampling 91 sentences (test91), while the second is randomly sampled 101 sentences from the longes... | Provide a detailed description of the following dataset: Dubbing Test Set |
Regensburg Pediatric Appendicitis Dataset | This dataset was acquired in a retrospective study from a cohort of pediatric patients admitted with abdominal pain to Childrenโs Hospital St. Hedwig in Regensburg, Germany. Multiple abdominal B-mode ultrasound images were acquired for most patients, with the number of views varying from 1 to 15. The images depict vari... | Provide a detailed description of the following dataset: Regensburg Pediatric Appendicitis Dataset |
PS4 | A dataset of 18,731 proteins with their PDB code, index of the first residue in their respective DSSP file, their residue sequence and 9-category secondary structure sequence (including polyproline helices). | Provide a detailed description of the following dataset: PS4 |
Persian-ATIS | The PATIS is a Persian language dataset for intent detection and slot filling. | Provide a detailed description of the following dataset: Persian-ATIS |
OpenD5 | **OpenD5** is a a meta-dataset which aggregates 675 open-ended problems ranging across business, social sciences, humanities, machine learning, and health, and uses a set of unified evaluation metrics: validity, relevance, novelty, and significance. It is designed for the new task, D5, that automatically discovers diff... | Provide a detailed description of the following dataset: OpenD5 |
DELIVER | **DELIVER** is an arbitrary-modal segmentation benchmark, covering Depth, LiDAR, multiple Views, Events, and RGB. Aside from this, the dataset is also used in four severe weather conditions as well as five sensor failure cases to exploit modal complementarity and resolve partial outages. It is designed for the tasks of... | Provide a detailed description of the following dataset: DELIVER |
MCubeS | Multimodal material segmentation (MCubeS) dataset contains 500 sets of images from 42 street scenes. Each scene has images for four modalities: RGB, angle of linear polarization (AoLP), degree of linear polarization (DoLP), and near-infrared (NIR). The dataset provides annotated ground truth labels for both material an... | Provide a detailed description of the following dataset: MCubeS |
MuscleMap136 | **MuscleMap136** is a dataset for video-based Activated Muscle Group Estimation (AMGE) aiming at identifying currently activated muscular regions of humans performing a specific activity. Video-based AMGE is an important yet overlooked problem. To this intent, the MuscleMap136 dataset features 15K video clips with 136 ... | Provide a detailed description of the following dataset: MuscleMap136 |
Data for: Employing Partial Least Squares Regression with Discriminant Analysis for Bug Prediction | For creating, optimizing, and evaluating our statistical model, we used the Public Unified Bug Dataset for Java. It contains the data entries of 5 different public bug datasets (PROMISE, Eclipse Bug Dataset, Bug Prediction Dataset, Bugcatchers Bug Dataset, and GitHub Bug Dataset) in a unified manner.
The dataset conta... | Provide a detailed description of the following dataset: Data for: Employing Partial Least Squares Regression with Discriminant Analysis for Bug Prediction |
RuWorldTree | RuWorldTree is a QA dataset with multiple-choice elementary-level science questions, which evaluate the understanding of core science facts.
**Motivation**
The WorldTree dataset starts the triad of the Reasoning and Knowledge tasks. The data includes the corpus of factoid utterances of various kinds, complex fact... | Provide a detailed description of the following dataset: RuWorldTree |
RuOpenBookQA | RuOpenBookQA is a QA dataset with multiple-choice elementary-level science questions which probe the understanding of core science facts.
**Motivation**
RuOpenBookQA is mainly based on the work of (Mihaylov et al., 2018): it is a QA dataset with multiple-choice elementary-level science questions, which probe the ... | Provide a detailed description of the following dataset: RuOpenBookQA |
MultiQ | MultiQ is a multi-hop QA dataset for Russian, suitable for general open-domain question answering, information retrieval, and reading comprehension tasks.
**Motivation**
Question-answering has been an essential task in natural language processing and information retrieval. However, certain areas in QA remain quit... | Provide a detailed description of the following dataset: MultiQ |
CheGeKa | CheGeKa is a Jeopardy!-like Russian QA dataset collected from the official Russian quiz database ChGK.
**Motivation**
The task can be considered the most challenging in terms of reasoning, knowledge and logic, as the task implies the QA pairs with a free response form (no answer choices); however, a long chain of... | Provide a detailed description of the following dataset: CheGeKa |
Ethics 2 | Ethics2 (per 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. The main objective of the task is to evaluate the positive or negative implementation of five concepts in... | Provide a detailed description of the following dataset: Ethics 2 |
Winograd Automatic | The Winograd schema challenge composes tasks with syntactic ambiguity, which can be resolved with logic and reasoning.
**Motivation**
The dataset presents an extended version of a traditional Winograd challenge (Levesque et al., 2012): each sentence contains unresolved homonymy, which can be resolved based on com... | Provide a detailed description of the following dataset: Winograd Automatic |
AdvNet | AdvNet is a dataset of traffic signs images. Specifically, it includes adversarial traffic sign images (i.e., pictures of traffic signs with stickers on their surface) that can fool state-of-the-art neural network-based perception systems and clean traffic sign images without any stickers on them.
If you use AdvNet,... | Provide a detailed description of the following dataset: AdvNet |
Cam-CAN | The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) is a large-scale collaborative research project at the University of Cambridge, launched in October 2010, with substantial initial funding from the Biotechnology and Biological Sciences Research Council (BBSRC), followed by support from the Medical Research Cou... | Provide a detailed description of the following dataset: Cam-CAN |
TRR360D | **TRR360D** is based on the ICDAR2019MTD modern table detection dataset, it refers to the annotation format of the DOTA dataset. The training set contains 600 rotated images and 977 annotated instances, and the test set contains 240 rotated images and 499 annotated instances. | Provide a detailed description of the following dataset: TRR360D |
UESTC-MMEA-CL | UESTC-MMEA-CL is a new multi-modal activity dataset for continual egocentric activity recognition, which is proposed to promote future studies on continual learning for first-person activity recognition in wearable applications. Our dataset provides not only vision data with auxiliary inertial sensor data but also comp... | Provide a detailed description of the following dataset: UESTC-MMEA-CL |
IoT-23 | IoT-23 is a dataset of network traffic from Internet of Things (IoT) devices. It has 20 malware captures executed in IoT devices, and 3 captures for benign IoT devices traffic. It was first published in January 2020, with captures ranging from 2018 to 2019. These IoT network traffic was captured in the Stratosphere Lab... | Provide a detailed description of the following dataset: IoT-23 |
Spring | **Spring** is a large, high-resolution and high-detail, computer-generated benchmark for scene flow, optical flow, and stereo. Based on rendered scenes from the open-source Blender movie "Spring", it provides photo-realistic HD datasets with state-of-the-art visual effects and ground truth training data. | Provide a detailed description of the following dataset: Spring |
FluidLab | **FluidLab** is a simulation environment with a diverse set of manipulation tasks involving complex fluid dynamics. These tasks address interactions between solid and fluid as well as among multiple fluids. | Provide a detailed description of the following dataset: FluidLab |
OpenASL | Large-scale American Sign Language (ASL) - English dataset collected from online video sites (e.g., YouTube). OpenASL contains 288 hours of ASL videos in multiple domains from over 200 signers. | Provide a detailed description of the following dataset: OpenASL |
ChatGPT Software Testing Study | **ChatGPT Software Testing Study Dataset** contains questions from a well-known software testing book by Ammann and Offutt. It uses all the textbook questions in Chapters 1 to 5 that have solutions available on the bookโs official website. These solutions are made publicly available to help students learn. Questions th... | Provide a detailed description of the following dataset: ChatGPT Software Testing Study |
VTQA | VTQA is a dataset containing open-ended questions about image-text pairs. This dataset requires the model to align multimedia representations of the same entity to implement multi-hop reasoning between image and text and finally use natural language to answer the question. The aim of this dataset is to develop and benc... | Provide a detailed description of the following dataset: VTQA |
CCEDD | We construct a largest publicly Cervical Cell Edge Detection Dataset (CCEDD) based on our Local Label Point Correction (LLPC). Our dataset is ten times larger than the previous datasets, which greatly facilitates the development of overlapping cell edge detection.
Paper: Local Label Point Correction for Edge Detecti... | Provide a detailed description of the following dataset: CCEDD |
NTLNP | This is an image dataset for object detection of wildlife in the mixed coniferous broad-leaved forest.
A total of 25,657 images in this dataset were generated from video clips taken by infrared cameras in the Northeast Tiger and Leopard National Park, including 17 main species (15 wild animals and 2 major domestic a... | Provide a detailed description of the following dataset: NTLNP |
UR5 Tool Dataset | In this dataset UR5 robot used 6 tools: metal-scissor, metal-whisk, plastic-knife, plastic-spoon, wooden-chopstick, and wooden-fork to perform 6 behaviors: look, stirring-slow, stirring-fast, stirring-twist, whisk, and poke. The robot explored 15 objects: cane-sugar, chia-seed, chickpea, detergent, empty, glass-bead, k... | Provide a detailed description of the following dataset: UR5 Tool Dataset |
3DOH50K | 3DOH50K is the first real 3D human dataset for the problem of human reconstruction and pose estimation in occlusion scenarios. It contains 51600 images with accurate 2D pose and 3D pose, SMPL parameters, and binary mask. | Provide a detailed description of the following dataset: 3DOH50K |
Jung | Dataset for document shadow removal | Provide a detailed description of the following dataset: Jung |
VNAT | This dataset is a collection of labelled PCAP files, both encrypted and unencrypted, across 10 applications, as well as a pandas dataframe in HDF5 format containing detailed metadata summarizing the connections from those files. It was created to assist the development of machine learning tools that would allow operato... | Provide a detailed description of the following dataset: VNAT |
Kligler | Dataset for document shadow removal | Provide a detailed description of the following dataset: Kligler |
AutoFR Dataset | **AutoFR Dataset** is broken down by each site that we crawl within a zip file. It contains multiple different experiments that we conducted in our paper. The overall dataset contains 1042 sites that we crawled where we detected ads within the Top-5K. | Provide a detailed description of the following dataset: AutoFR Dataset |
FMD (materials) | Sharan, Lavanya, Ruth Rosenholtz, and Edward Adelson.
"Material perception: What can you see in a brief glance?."
Journal of Vision 9.8 (2009): 784-784.
http://people.csail.mit.edu/celiu/CVPR2010/FMD/FMD.zip | Provide a detailed description of the following dataset: FMD (materials) |
MobileBrick | Generate high-quality 3D ground-truth shapes for reconstruction evaluation is extremely challenging because even 3D scanners can only generate pseudo ground-truth shapes with artefacts. We propose a novel data capturing and 3D annotation pipeline to obtain precise 3D ground-truth shapes without relying on expensive 3D ... | Provide a detailed description of the following dataset: MobileBrick |
X-Humans | **X-Humans** consists of 20 subjects (11 males, 9 females) with various clothing types and hair style. The collection of this dataset has been approved by an internal ethics committee. For each subject, we split the motion sequences into a training and test set. In total, there are 29,036 poses for training and 6,439 t... | Provide a detailed description of the following dataset: X-Humans |
IoTCheck Dataset | https://github.com/uci-plrg/iotcheck-data | Provide a detailed description of the following dataset: IoTCheck Dataset |
OVRseen | https://athinagroup.eng.uci.edu/projects/ovrseen/ | Provide a detailed description of the following dataset: OVRseen |
PubChem18 | A.2.1 AN OPEN, LARGE-SCALE DATASET FOR ZERO-SHOT DRUG DISCOVERY DERIVED FROM PUBCHEM
We constructed a large public dataset extracted from PubChem (Kim et al., 2019; Preuer et al., 2018), an open chemistry
database, and the largest collection of readily available chemical data. We take assays ranging from 2004 to 2018... | Provide a detailed description of the following dataset: PubChem18 |
LPSC | This data set contains annotated text versions of 1635 two-page abstracts published at the Lunar and Planetary Science Conference from 1998 to 2020 of relevance to four Mars missions. The annotations were generated using named entity recognition and relation extraction provided by the MTE processing pipeline (availabl... | Provide a detailed description of the following dataset: LPSC |
1DSfM | The 1DSfM Landmarks is a collection of community-based image reconstruction by Kyle Wilson and is comprised of 14 datasets with comparison to bundler ground truth. Notredame is provided separately. Datasets (tar.gz, 642 MB) Alamo images (tar, 2.0 GB) Ellis Island images (tar, 1.6 GB) Madrid Metropolis images (tar, 0.7 ... | Provide a detailed description of the following dataset: 1DSfM |
CCv2 | **Casual Conversations v2 (CCv2)** is composed of over 5,567 participants (26,467 videos) and intended mainly to be used for assessing the performance of already trained models in computer vision and audio applications for the purposes permitted in our data license agreement. The videos feature paid individuals who agr... | Provide a detailed description of the following dataset: CCv2 |
COCO-MLT | The COCO-MLT is created from MS COCO-2017, containing 1,909 images from 80 classes. The maximum of training number per class is 1,128 and the minimum is 6. We use the test set of COCO2017 with 5,000 for evaluation. The ratio of head, medium, and tail classes is 22:33:25 in COCO-MLT. | Provide a detailed description of the following dataset: COCO-MLT |
VOC-MLT | We construct the long-tailed version of VOC from its 2012 train-val set. It contains 1,142 images from 20 classes, with a maximum of 775 images per class and a minimum of 4 images per class. The ratio of head, medium, and tail classes after splitting is 6:6:8. We evaluate the performance on VOC2007 test set with 4952... | Provide a detailed description of the following dataset: VOC-MLT |
CHAD | # CHAD: Charlotte Anomaly Dataset
CHAD is high-resolution, multi-camera dataset for surveillance video anomaly detection. It includes bounding box, Re-ID, and pose annotations, as well as frame-level anomaly labels, dividing all frames into two groups of anomalous or normal. You can find the paper with all the detai... | Provide a detailed description of the following dataset: CHAD |
FEE Corridor | The data set contains point cloud data captured in an indoor environment with precise localization and ground truth mapping information.
Two โstop-and-goโ data sequences of a robot with mounted Ouster OS1-128 lidar are provided.
This data-capturing strategy allows recording lidar scans that do not suffer from an erro... | Provide a detailed description of the following dataset: FEE Corridor |
CLOTH3D | This work presents CLOTH3D, the first big scale synthetic dataset of 3D clothed human sequences. CLOTH3D contains a large variability on garment type, topology, shape, size, tightness and fabric. Clothes are simulated on top of thousands of different pose sequences and body shapes, generating realistic cloth dynamics. ... | Provide a detailed description of the following dataset: CLOTH3D |
Fashion-MNIST-H | We provide multiple human annotations for each test image in Fashion-MNIST. This can be used as soft labels or probabilistic labels instead of the usual hard (single) labels. | Provide a detailed description of the following dataset: Fashion-MNIST-H |
MGTAB | **MGTAB** is the first standardized graph-based benchmark for stance and bot detection. MGTAB contains 10,199 expert-annotated users and 7 types of relationships, ensuring high-quality annotation and diversified relations. For more details, please refer to the MGTAB paper. | Provide a detailed description of the following dataset: MGTAB |
ATMโ22 | **ATM'22** is a multi-site, multi-domain dataset for pulmonary airway segmentation. It contains large-scale CT scans with detailed pulmonary airways annotation, including 500 CT scans (300 for training, 50 for validation, and 150 for testing). The dataset was collected from different sites and it further included a por... | Provide a detailed description of the following dataset: ATMโ22 |
Med-EASi | Med-EASi (Medical dataset for Elaborative and Abstractive Simplification), a uniquely crowdsourced and finely annotated dataset for supervised simplification of short medical texts. It contains 1979 expert-simple text pairs in medical domain, spanning a total of 4478 UMLS concepts across all text pairs. The dataset is ... | Provide a detailed description of the following dataset: Med-EASi |
Real-World Stereo Color and Sharpness Mismatch Dataset | A real-world stereo video dataset, containing 1200 frame pairs with real-world color and sharpness mismatches caused by beam splitter.
Color and sharpness mismatches between views of the stereoscopic 3D video can decrease the overall video quality and may cause viewer discomfort and headaches. To eliminate this prob... | Provide a detailed description of the following dataset: Real-World Stereo Color and Sharpness Mismatch Dataset |
DeSmoke-LAP dataset | The laparoscopic surgery dataset is associated with our International Journal of Computer Assisted Radiology and Surgery (IJCARS) publication titled โDeSmoke-LAP: Improved Unpaired Image-to-Image Translation for Desmoking in Laparoscopic Surgeryโ. The training model of the proposed method is available as an open source... | Provide a detailed description of the following dataset: DeSmoke-LAP dataset |
SESYD Dataset | SESYD "Systems Evaluation SYnthetic Documents" is a database of synthetical documents with groundtruth. This database targets two main research problems in the document image analysis field (i) symbol recognition and spotting in line drawing images (floorplans and electrical diagrams) (ii) character segmentation and re... | Provide a detailed description of the following dataset: SESYD Dataset |
VisA | The VisA dataset contains 12 subsets corresponding to 12 different objects as shown in the above figure. There are 10,821 images with 9,621 normal and 1,200 anomalous samples. Four subsets are different types of printed circuit boards (PCB) with relatively complex structures containing transistors, capacitors, chips, e... | Provide a detailed description of the following dataset: VisA |
Uncertainty and Concept Drift | AI-based digital twins are at the leading edge of theIndustry 4.0 revolution, which are technologically empowered bythe Internet of Things and real-time data analysis. Information
collected from industrial assets is produced in a continuous fashion, yielding data streams that must be processed under stringent timing c... | Provide a detailed description of the following dataset: Uncertainty and Concept Drift |
V2V4Real | **V2V4Real** is a large-scale real-world multi-modal dataset for V2V perception. The data is collected by two vehicles equipped with multi modal sensors driving together through diverse scenarios. It covers a driving area of 410 km comprising 20K LiDAR frames, 40K RGB frames, 240K annotated 3D bounding boxes for 5 clas... | Provide a detailed description of the following dataset: V2V4Real |
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