dataset_name stringlengths 2 128 | description stringlengths 1 9.7k | prompt stringlengths 59 185 |
|---|---|---|
Top-N Recommendation Runs | We ran 21 recommender systems on three datasets (BeerAdvocate, LibraryThing and MovieLens 1M). The output of these recommenders was evaluated using rec_eval tool. We also measured statistically significant improvements using permutation test. The output of both tools can be found in data. | Provide a detailed description of the following dataset: Top-N Recommendation Runs |
TREC Ad Hoc Retrieval Runs (2020) | TREC Submissions for all Ad Hoc Retrieval runs.
core (2017-2018)
deep-docs (2019-2020)
deep-pass (2019-2020)
web (2009-2014)
robust (2004) | Provide a detailed description of the following dataset: TREC Ad Hoc Retrieval Runs (2020) |
ChinaOpen-1k | ChinaOpen is a new video dataset targeted at open-world multimodal learning, with raw data gathered from Bilibili, a popular Chinese video-sharing website. The dataset has a large webly annotated training set of videos (associated with user-generated titles and tags) and a smaller manually annotated test set of videos ... | Provide a detailed description of the following dataset: ChinaOpen-1k |
Large-scale Ridesharing DARP Instances Based on Real Travel Demand | This dataset presents a set of large-scale ridesharing Dial-a-Ride Problem (DARP) instances. The instances were created as a standardized set of ridesharing DARP problems for the purpose of benchmarking and comparing different solution methods.
The instances are using actual past demand and realistic travel time dat... | Provide a detailed description of the following dataset: Large-scale Ridesharing DARP Instances Based on Real Travel Demand |
HumanEval-ET | Extension test cases of HumanEval, as well as generated code. | Provide a detailed description of the following dataset: HumanEval-ET |
MBPP-ET | Extension test cases of MBPP, as well as generated code. | Provide a detailed description of the following dataset: MBPP-ET |
APPS-ET | Extension test cases of APPS, as well as generated code. | Provide a detailed description of the following dataset: APPS-ET |
XGBoost | 123 | Provide a detailed description of the following dataset: XGBoost |
Szeged Corpus | The Szeged Treebank is the largest fully manually annotated treebank of the Hungarian language. It contains 82,000 sentences, 1.2 million words and 250,000 punctuation marks. Texts were selected from six different domains, ~200,000 words in size from each. The domains are the following:
fiction
compositions of pupi... | Provide a detailed description of the following dataset: Szeged Corpus |
Uncorrelated Corrupted Dataset | Uncorrelated Corrupted Dataset is an evaluation set that consists of realistic visible-infrared (V-I) corruptions allowing for models' corruption robustness evaluation. Initially proposed for multimodal person re-identification, our dataset can also be used for the evaluation of V-I cross-modal approaches. Corruptions ... | Provide a detailed description of the following dataset: Uncorrelated Corrupted Dataset |
Correlated Corrupted Dataset | Correlated Corrupted Dataset is an evaluation set that consists of realistic visible-infrared (V-I) corruptions allowing for models' corruption robustness evaluation. Initially proposed for multimodal person re-identification, our dataset can also be used for the evaluation of V-I cross-modal approaches. Corruptions of... | Provide a detailed description of the following dataset: Correlated Corrupted Dataset |
FaMoS | FaMoS is a dynamic 3D head dataset from 95 subjects, each performing 28 motion sequences. The sequences comprise of six prototypical expressions (i.e., Anger, Disgust, Fear, Happiness, Sadness, and Surprise), two head rotations (left/right and up/down), and diverse facial motions, including extreme and asymmetric expre... | Provide a detailed description of the following dataset: FaMoS |
Demande Dataset | **Demande Dataset** contains the features and probabilites of ten different functions. | Provide a detailed description of the following dataset: Demande Dataset |
FICLE | The FICLE dataset is a derivative of the FEVER dataset, which is a collection of 185,445 claims generated by modifying sentences obtained from Wikipedia. These claims were then verified without knowledge of the original sentences they were derived from. Each sample in the FEVER dataset consists of a claim sentence, a c... | Provide a detailed description of the following dataset: FICLE |
100STYLE | Over 4 million frames of motion capture data for 100 different styles of locomotion. Can be used for animation, human motion and sequence modelling research. | Provide a detailed description of the following dataset: 100STYLE |
GPABenchmark | GPT-generated and hum-written academic abstract corpus with over 600k samples in Computer Science, Physics, and Humanity Science. | Provide a detailed description of the following dataset: GPABenchmark |
YouTube8M-MusicTextClips | The YouTube8M-MusicTextClips dataset consists of over 4k high-quality human text descriptions of music found in video clips from the YouTube8M dataset.
For each selected YouTube music video, we extracted 10 second clips at the middle of the video for annotation. We provided annotators with only the audio correspondi... | Provide a detailed description of the following dataset: YouTube8M-MusicTextClips |
ACCT Data Repository | This dataset is a collection of fluorescent images from mice in order to test an automatic cell counting tool that we developed. 62 images viewed from 2 or 3 different fields of views are shown. In brief, the dataset was derived from brain sections of a model for HIV-induced brain injury (HIVgp120tg), which expresses s... | Provide a detailed description of the following dataset: ACCT Data Repository |
wiki | The dataset wiki consists of Wikipedia articles, where the goal is to predict the total page views of each article.
\# Nodes: 1,925,342,
\# Edges: 303,434,860,
\# Features: 600,
\# Classes: 5. | Provide a detailed description of the following dataset: wiki |
OxIOD | ## OxIOD Dataset
[Oxford Inertial Odometry Dataset](http://deepio.cs.ox.ac.uk/) [<a id="d1" href="#oxiod">1</a>] is a large set of inertial data for inertial odometry which is recorded by smartphones at 100 Hz in indoor environment. The suite consists of 158 tests and covers a distance of over 42 km, with OMC ground... | Provide a detailed description of the following dataset: OxIOD |
RONIN | ## RoNIN
The RoNIN dataset contains over 40 hours of IMU sensor data from 100 human subjects with 3D ground-truth trajectories under natural human movements. This data set provides measurements of the accelerometer, gyroscope, magnetometer, and ground track, including direction and location in 327 sequences and at a... | Provide a detailed description of the following dataset: RONIN |
RepoIMU | ## RepoIMU T-stick
The RepoIMU T-stick is a small, low-cost, and high-performance inertial measurement unit (IMU) that can be used for a wide range of applications. The RepoIMU T-stick is a 9-axis IMU that measures the acceleration, angular velocity, and magnetic field. This database contains two separate sets of ... | Provide a detailed description of the following dataset: RepoIMU |
Ekman6 | the YF-E6 emotion dataset using the 6 basic emotion type as keywords on social video-sharing websites including YouTube and Flickr, leading to a total of 3000 videos. The dataset is labeled through crowdsourcing by 10 different annotators (5 males and 5 females), whose age ranged from 22 to 45. Annotators were given de... | Provide a detailed description of the following dataset: Ekman6 |
MoB | A dataset of cartoon video clips. For each video clip, the presence or absence of each feature was marked by the annotators.
Malicious: Video content which may not be suitable for viewing by toddlers and pre-schoolers includes a set of clearly defined, trivial and intu-itive features as well as some comp... | Provide a detailed description of the following dataset: MoB |
ISOD | ISOD contains **2,000 manually labelled RGB-D images** from **20 diverse sites**, each featuring **over 30 types of small objects** randomly placed amidst the items already present in the scenes. These objects, **typically ≤3cm in height**, include LEGO blocks, rags, slippers, gloves, shoes, cables, crayons, chalk, gla... | Provide a detailed description of the following dataset: ISOD |
S2RDA | Our proposed Synthetic-to-Real benchmark for more practical visual DA (termed S2RDA) includes two challenging transfer tasks of S2RDA-49 and S2RDA-MS-39. In each task, source/synthetic domain samples are synthesized by rendering 3D models from ShapeNet. The used 3D models are in the same label space as the target/real ... | Provide a detailed description of the following dataset: S2RDA |
CIFAR-10C | Common corruptions dataset for CIFAR10 | Provide a detailed description of the following dataset: CIFAR-10C |
2DeteCT | Maximilian B. Kiss, Sophia B. Coban, K. Joost Batenburg, Tristan van Leeuwen, and Felix Lucka "2DeteCT - A large 2D expandable, trainable, experimental Computed Tomography dataset for machine learning", [Sci Data 10, 576 (2023)](https://doi.org/10.1038/s41597-023-02484-6) or [arXiv:2306.05907 (2023)](https://arxiv.org... | Provide a detailed description of the following dataset: 2DeteCT |
Uniref90 | UniRef90 is generated by clustering UniRef100 seed sequences.
The UniRef100 sequences shorter than 11 residues are excluded in UniRef90 clusters. Each UniRef90 cluster has one representative sequence from the UniRef100 database.
UniRef90 cluster titles and identifiers are derived from the representative UniRef100... | Provide a detailed description of the following dataset: Uniref90 |
maadaa-FaEco Dataset | The dataset is organized into 24 typical scenarios, showcasing the richness of real-world environments, conditions, and objects. It is carefully curated to reflect diverse and realistic situations, allowing models to be tested and refined under a wide range of conditions.
This dataset contains 33 meticulously fine-a... | Provide a detailed description of the following dataset: maadaa-FaEco Dataset |
MVP-24K | Multi-grained Vehicle Parsing (MVP) is a large-scale dataset for semantic analysis of vehicles in the wild, which has several featured properties.
1. The MVP contains 24,000 vehicle images captured in read-world surveillance scenes, which makes it more scalable for real applications.
2. For different requirements, we... | Provide a detailed description of the following dataset: MVP-24K |
Belfort | # The Belfort dataset
This dataset includes minutes of Belfort municipal council drawn up between 1790 and 1946. Documents include deliberations, lists of councillors, convocations, and agendas. It includes 24,105 text-line images that were automatically detected from pages. Up to 4 transcriptions are available for ... | Provide a detailed description of the following dataset: Belfort |
AMIGOS | We present a database for research on affect, personality traits and mood by means of neuro-physiological signals. Different to other databases, we elicited affect using both short and long videos in two configurations, one with individual viewers and one with groups of viewers. The database allows the multimodal study... | Provide a detailed description of the following dataset: AMIGOS |
MagicBrush | **MagicBrush** is a manually-annotated instruction-guided image editing dataset covering diverse scenarios single-turn, multi-turn, mask-provided, and mask-free editing. MagicBrush comprises 10K (source image, instruction, target image) triples, which is sufficient to train large-scale image editing models. | Provide a detailed description of the following dataset: MagicBrush |
OCTScenes | **OCTScenes** contains 5000 tabletop scenes with a total of 15 everyday objects. Each scene is captured in 60 frames covering a 360-degree perspective.
OCTScenes-A dataset, the 0--3099 scenes without segmentation annotation are for training, while the 3100--3199 scenes with segmentation annotation can be used for te... | Provide a detailed description of the following dataset: OCTScenes |
Im-Promptu Visual Analogy Suite | **Im-Promptu Visual Analogy Suite** is a meta-learning framework. Each visual analogy suite is divided into two broad kind of analogies depending on the underlying relation - Primitive and Composite tasks
(1) Primitive: A single image attribute is modified at a time. For example, the color of the object is changed f... | Provide a detailed description of the following dataset: Im-Promptu Visual Analogy Suite |
MSVD-Indonesian | MSVD-Indonesian is derived from the MSVD dataset, which is obtained with the help of a machine translation service. This dataset can be used for multimodal video-text tasks, including text-to-video retrieval, video-to-text retrieval, and video captioning. Same as the original English dataset, the MSVD-Indonesian datase... | Provide a detailed description of the following dataset: MSVD-Indonesian |
DACCORD | DACCORD is a new dataset dedicated to the task of automatically detecting contradictions between sentences in French.
The dataset is currently composed of 1034 sentence pairs. It covers the themes of Russia’s invasion of Ukraine in 2022, the Covid-19 pandemic, and the climate crisis. | Provide a detailed description of the following dataset: DACCORD |
GenPlot | This dataset contains the pre-generated dataset referenced in the GenPlot Paper.
## 5 Chart Types
There are 5 subfolders in this dataset containing 100_000 plots. Each subfolder corresponds to the each chart type.
l = line
v = vertical_bar
h = horizontal_bar
s = scatter
d = dot
## Metadata
T... | Provide a detailed description of the following dataset: GenPlot |
COVID-19 Vaccine Stance Dataset | The data contains CSV files with anonymized user names, tweet texts, vaccine stance, cumulative score for the vaccine stance, location, and topic information. The file named `all_predicted_cumulative_stance.csv` contains all the tweets, scores, and classifications. We have broken this file into two separate files named... | Provide a detailed description of the following dataset: COVID-19 Vaccine Stance Dataset |
Labelling for Explosions and Road accidents from UCF-Crime | The whole UCF-Crime dataset consists of real-world 240 × 320 RGB videos with 13 realistic anomaly types such as explosion, road accident, burglary, etc., and normal examples. The CPD specific requires a change in data distribution. We suppose that explosions and road accidents correspond to such a scenario, while most ... | Provide a detailed description of the following dataset: Labelling for Explosions and Road accidents from UCF-Crime |
Waymo Open Motion Dataset | As autonomous driving systems mature, motion forecasting has received increasing attention as a critical requirement for planning. Of particular importance are interactive situations such as merges, unprotected turns, etc., where predicting individual object motion is not sufficient. Joint predictions of multiple objec... | Provide a detailed description of the following dataset: Waymo Open Motion Dataset |
CASIE | ### Annotation corpus of cybersecurity event in news articles
The corpus contains 1000 annotation and source files. Our cybersecurity focused on five event types: Databreach, Phishing, Ransom, Discover, and Patch.
More details of the annotation and CASIE's system are in the papers. If you use our data, please cit... | Provide a detailed description of the following dataset: CASIE |
Face dataset by Generated Photos | The free Face dataset made for students and teachers. It contains 10,000 photos with equal distribution of race and gender parameters, along with metadata and facial landmarks. Free to use for research with citation Photos by Generated.Photos.
Photos
All the photos are 100% synthetic. Based on model-released ph... | Provide a detailed description of the following dataset: Face dataset by Generated Photos |
Regex101 Regular expressions | This is a dataset of regular expressions collected from regex101.com. It is not made directly available, but can be [crawled from regex101](https://github.com/dataunitylab/semantic-regex). | Provide a detailed description of the following dataset: Regex101 Regular expressions |
Boson-nighttime | In order to collect thermal aerial data, we used FLIR's Boson thermal imager (8.7 mm focal length, 640p resolution, and $50^\circ$ horizontal field of view)\footnote{\url{https://www.flir.es/products/boson/}}. The collected images are nadir at approx. 1m/px spatial resolution. We performed six flights from 9:00 PM to 4... | Provide a detailed description of the following dataset: Boson-nighttime |
CompMix | **CompMix** is a crowdsourced QA benchmark which naturally demands the integration of a mixture of input sources. CompMix has a total of 9,410 questions, and features several complex intents like joins and temporal conditions. | Provide a detailed description of the following dataset: CompMix |
ToolQA | **ToolQA** is a question answering benchmark for Large Language Models (LLMs) which is designed to faithfully evaluate LLMs' ability to use external tools for question answering. The development of ToolQA involved a scalable, automated process for dataset curation, along with 13 specialized tools designed for interacti... | Provide a detailed description of the following dataset: ToolQA |
DISCO-10M | DISCO-10M is a novel and extensive music dataset that surpasses the largest previously available music dataset by an order of magnitude. | Provide a detailed description of the following dataset: DISCO-10M |
MI-Motion | **Multi-Person Interaction Motion (MI-Motion) Dataset** includes skeleton sequences of multiple individuals collected by motion capture systems and refined and synthesized using a game engine. The dataset contains 167k frames of interacting people's skeleton poses and is categorized into 5 different activity scenes. | Provide a detailed description of the following dataset: MI-Motion |
SMART-101 | Recent times have witnessed an increasing number of applications of deep neural networks towards solving tasks that require superior cognitive abilities, e.g., playing Go, generating art, ChatGPT, etc. Such a dramatic progress raises the question: how generalizable are neural networks in solving problems that demand br... | Provide a detailed description of the following dataset: SMART-101 |
DeepGraviLens | DeepGraviLens is a data set of simulated gravitational lenses consisting of images associated with brightness variation time series. In this dataset, both non-transient and transient phenomena (supernovae explosions) are simulated. | Provide a detailed description of the following dataset: DeepGraviLens |
Blood Cell Detection Dataset | ## Overview
This is a dataset of blood cells photos.
There are 364 images across three classes: `WBC` (white blood cells), `RBC `(red blood cells), and `Platelets`. There are 4888 labels across 3 classes (and 0 null examples).
Fork this dataset (upper right hand corner) to receive the raw images, or (to save spa... | Provide a detailed description of the following dataset: Blood Cell Detection Dataset |
Yelp Review Polarity | The Yelp Reviews Polarity dataset is obtained from the Yelp Dataset Challenge in 2015 (1,569,264 samples that have review text).
The polarity label is constructed by considering stars 1 and 2 negative, and 3 and 4 positive.
The polarity dataset has 280,000 training samples and 19,000 test samples in each polarity... | Provide a detailed description of the following dataset: Yelp Review Polarity |
L3Cube-MahaCorpus | **L3Cube-MahaCorpus** is a Marathi monolingual data set scraped from different internet sources. We expand the existing Marathi monolingual corpus with 24.8M sentences and 289M tokens. We also present, MahaBERT, MahaAlBERT, and MahaRoBerta all BERT-based masked language models, and MahaFT, the fast text word embeddings... | Provide a detailed description of the following dataset: L3Cube-MahaCorpus |
PTVD | **PTVD** is a plot-oriented multimodal dataset in the TV domain. It is also the first non-English dataset of its kind. Additionally, PTVD contains more than 26 million bullet screen comments (BSCs), powering large-scale pre-training. | Provide a detailed description of the following dataset: PTVD |
FunQA | **FunQA** is a challenging video question answering (QA) dataset specifically designed to evaluate and enhance the depth of video reasoning based on counter-intuitive and fun videos. Unlike most video QA benchmarks which focus on less surprising contexts, e.g., cooking or instructional videos, FunQA covers three previo... | Provide a detailed description of the following dataset: FunQA |
UNIPD-BPE | The University of Padova Body Pose Estimation dataset (UNIPD-BPE) is an extensive dataset for multi-sensor body pose estimation containing both single-person and multi-person sequences with up to 4 interacting people
A network with 5 Microsoft Azure Kinect RGB-D cameras is exploited to record synchronized high-definit... | Provide a detailed description of the following dataset: UNIPD-BPE |
EgoISM-HOI | EgoISM-HOI is a new multimodal dataset composed of synthetic and real images of egocentric human-objects interactions in an industrial environment with rich annotations of hands and objects. EgoISM-HOI contains a total of 39,304 RGB images, 23,356 depth maps and instance segmentation masks, 59,860 hand annotations, 237... | Provide a detailed description of the following dataset: EgoISM-HOI |
LGP | Generated for further pre-training pre-trained models like BERT, RoBERTa, ALBERT, DeBERTa, etc.. in order to get stronger logical reasoning ability. | Provide a detailed description of the following dataset: LGP |
GUE | A collection of $28$ datasets across $7$ tasks constructed for genome language model evaluation. Contains seven tasks: promoter prediction. core promoter prediction, splice site prediction, covid variant classification, epigenetic marks prediction, and transcription factor binding sites prediction on human and mouse. | Provide a detailed description of the following dataset: GUE |
WDC Block | WDC Block is a benchmark for comparing the performance of blocking methods that are used as part of entity resolution pipelines.
Entity resolution aims to identify records in two datasets (A and B) that describe the same real-world entity. Since comparing all record pairs between two datasets can be computationally ... | Provide a detailed description of the following dataset: WDC Block |
3D-Speaker | **3D-Speaker** is a large-scale speech corpus designed to facilitate the research of speech representation disentanglement. 3DSpeaker contains over 10,000 speakers, each of whom are simultaneously recorded by multiple Devices, locating at different Distances, and some speakers are speaking multiple Dialects. The contro... | Provide a detailed description of the following dataset: 3D-Speaker |
ShuttleSet22 | **ShuttleSet22** is a badminton singles dataset which is collected from high-ranking matches in 2022. ShuttleSet22 consists of 30,172 strokes in 2,888 rallies in the training set, 1,400 strokes in 450 rallies in validation set, and 2,040 strokes in 654 rallies in testing set with detailed stroke-level metadata within a... | Provide a detailed description of the following dataset: ShuttleSet22 |
YouTube-ASL | **YouTube-ASL** is a large-scale, open-domain corpus of American Sign Language (ASL) videos and accompanying English captions drawn from YouTube. With ~1000 hours of videos and >2500 unique signers, YouTube-ASL is ~3x as large and has ~10x as many unique signers as the largest prior ASL dataset. | Provide a detailed description of the following dataset: YouTube-ASL |
RoseBlooming-Dataset | The RoseBlooming dataset is a stage-specific flower dataset for detection. The dataset, consisting of overhead images, contains two rose cultivars and was filmed over a period of months.
The dataset has 519 images, and most of the images contain several bounding boxes. Therefore, this dataset contains over 7,000 boun... | Provide a detailed description of the following dataset: RoseBlooming-Dataset |
N-back-tasks-for-ChatGPT | **Dataset Introduction.** We create this dataset to test the working memory capacity of language models. We choose the N-back task because it is widely used in cognitive science as a measure of working memory capacity. To create the N-back task dataset, we generated 30 blocks of trials for $N = \{1, 2, 3\}$, respective... | Provide a detailed description of the following dataset: N-back-tasks-for-ChatGPT |
GlobalOpinionQA | **GlobalOpinionQA** consists of questions and answers from cross-national surveys designed to capture diverse opinions on global issues across different countries. It contains a subset of survey questions about global issues and opinions adapted from the World Values Survey and Pew Global Attitudes Survey. | Provide a detailed description of the following dataset: GlobalOpinionQA |
GEM HOUSE OPENDATA | Filip Milojkovic, August 13, 2021, "GEM HOUSE openData: German Electricity consumption in Many HOUSEholds over three years 2018-2020 (Fresh Energy)", IEEE Dataport, doi: https://dx.doi.org/10.21227/4821-vf03. | Provide a detailed description of the following dataset: GEM HOUSE OPENDATA |
UTRSet-Real | The **UTRSet-Real** dataset is a comprehensive, manually annotated dataset specifically curated for **Printed Urdu OCR** research. It contains over **11,000** printed text line images, each of which has been meticulously annotated. One of the standout features of this dataset is its remarkable diversity, which includes... | Provide a detailed description of the following dataset: UTRSet-Real |
UTRSet-Synth | The **UTRSet-Synth** dataset is introduced as a complementary training resource to the [**UTRSet-Real** Dataset](https://paperswithcode.com/dataset/utrset-real), specifically designed to enhance the effectiveness of Urdu OCR models. It is a high-quality synthetic dataset comprising 20,000 lines that closely resemble re... | Provide a detailed description of the following dataset: UTRSet-Synth |
FLIP | FLIP includes several benchmark datasets that contain a variety of protein sequences, each with a real-valued label indicating its "fitness" (how well the protein performs some particular function). The goal is to predict the fitness of a given protein sequence using the sequence. Different representations of protein s... | Provide a detailed description of the following dataset: FLIP |
UrduDoc | The **UrduDoc Dataset** is a benchmark dataset for Urdu text line detection in scanned documents. It is created as a byproduct of the **UTRSet-Real** dataset generation process. Comprising 478 diverse images collected from various sources such as books, documents, manuscripts, and newspapers, it offers a valuable resou... | Provide a detailed description of the following dataset: UrduDoc |
FLIP -- AAV, Designed vs mutant | FLIP includes several benchmark datasets that contain a variety of protein sequences, each with a real-valued label indicating its "fitness" (how well the protein performs some particular function). The goal is to predict the fitness of a given protein sequence using the sequence. Different representations of protein s... | Provide a detailed description of the following dataset: FLIP -- AAV, Designed vs mutant |
Hurricane | a new spatio-temporal benchmark dataset (Hurricane), which is suited for forecasting during extreme events and anomalies. The dataset is provided through the Florida Department of Revenue which provides the monthly sales revenue (2003-2020) for the tourism industry for all 67 counties of Florida which are prone to annu... | Provide a detailed description of the following dataset: Hurricane |
Finance | State-level data for USA. The changes in the number of employees based on one million employees active in the US during the COVID-19
pandemic and is gathered from Homebase (Bartik et al. 2020). We further enriched
the data with the state-level policies as an indication of extreme events (e.g., the
state’s business c... | Provide a detailed description of the following dataset: Finance |
Climabench | The topic of Climate Change (CC) has received limited attention in NLP despite its real world urgency. Activists and policy-makers need NLP tools in order to effectively process the vast and rapidly growing textual data produced on CC. Their utility, however, primarily depends on whether the current state-of-the-art mo... | Provide a detailed description of the following dataset: Climabench |
S1SLC_CVDL | ABSTRACT
Development of the Complex-Valued (CV) deep learning architectures has enabled us to exploit the amplitude and phase components of the CV Synthetic Aperture Radar (SAR) data. However, most of the available annotated SAR datasets provide only the amplitude information (Only detected SAR data) and disregard th... | Provide a detailed description of the following dataset: S1SLC_CVDL |
Drunkard's Dataset | Estimating camera motion in deformable scenes poses a complex and open research challenge. Most existing non-rigid structure from motion techniques assume to observe also static scene parts besides deforming scene parts in order to establish an anchoring reference. However, this assumption does not hold true in certain... | Provide a detailed description of the following dataset: Drunkard's Dataset |
BEDLAM | **BEDLAM** is a large-scale synthetic video dataset designed to train and test algorithms on the task of 3D human pose and shape estimation (HPS). It contains diverse body shapes, skin tones, and motions. The clothing is realistically simulated on the moving bodies using commercial clothing physics simulation. | Provide a detailed description of the following dataset: BEDLAM |
OASST1 | **license**:
apache-2.0
**tags**:
human-feedback
**size_categories**:
100K<n<1M
**pretty_name**:
OpenAssistant Conversations
# OpenAssistant Conversations Dataset (OASST1)
## Dataset Description
- **Homepage:** https://www.open-assistant.io/
- **Repository:** https://github.com/LAION-AI/Open-Assistant
... | Provide a detailed description of the following dataset: OASST1 |
NBMOD | ## Introduction
NBMOD is a dataset created for researching the task of specific object grasp detection by robots in noisy environments. The dataset comprises three subsets: Simple background Single-object Subset (SSS), Noisy background Single-object Subset (NSS), and Multi-Object grasp detection Subset (MOS). The SS... | Provide a detailed description of the following dataset: NBMOD |
GUG | See article for detail | Provide a detailed description of the following dataset: GUG |
VFD-2000 | **VFD-2000** is a video fight detection dataset containing more than 2000 videos. YouTube is the data source. Specific scenarios are searched using “fight” as a search keyword, for example, “street fight”, “beach fight”, and “violence in the restaurant”. 200 videos under 20 different scenes are collected. | Provide a detailed description of the following dataset: VFD-2000 |
V-LoL-Trains | Despite the successes of recent developments in visual AI, different shortcomings still exist; from missing exact logical reasoning, to abstract generalization abilities, to understanding complex and noisy scenes. Unfortunately, existing benchmarks, were not designed to capture more than a few of these aspects. Whereas... | Provide a detailed description of the following dataset: V-LoL-Trains |
R&D Datasets for solving event combinatorics in all hadronic top quark pair events at the LHC | Used in the development of Topographs: Topological Reconstruction of Particle Physics Processes using Graph Neural Networks
The datasets contain 5.8M ttbar events in the all hadronic decay channel, with jets matched to the truth partons in the top quark decays. | Provide a detailed description of the following dataset: R&D Datasets for solving event combinatorics in all hadronic top quark pair events at the LHC |
DiaSafety | **DiaSafety** is a comprehensive dialogue safety dataset. It consists of 11K contextual dialogues under 7 unsafe subaspects in chitchat. | Provide a detailed description of the following dataset: DiaSafety |
TomoSAM | A dataset made of 3D image data and their embeddings to test TomoSAM | Provide a detailed description of the following dataset: TomoSAM |
Dissonance Twitter Dataset | **Dissonance Twitter Dataset** is a dataset collected from annotating tweets for dissonance. | Provide a detailed description of the following dataset: Dissonance Twitter Dataset |
Simple Shapes Dataset | It consists of 32x32 pixel images of shapes with multiple attributes (size, location, rotation, color). Each image is also paired with its ground truth information (attributes), and a natural language description (English) of the image.
The dataset is composed of:
a train set of 500,000 samples,
a val and ... | Provide a detailed description of the following dataset: Simple Shapes Dataset |
3D-POP | The dataset is designed specifically to solve a range of computer vision problems (2D-3D tracking, posture) faced by biologists while designing behavior studies with animals.
Typically, datasets for animal-specific vision tasks are created using open-source video material. This might be effective for an initial star... | Provide a detailed description of the following dataset: 3D-POP |
UT-Zappos50K | UT Zappos50K (UT-Zap50K) is a large shoe dataset consisting of 50,025 catalog images collected from Zappos.com. The images are divided into 4 major categories — shoes, sandals, slippers, and boots — followed by functional types and individual brands. The shoes are centered on a white background and pictured in the same... | Provide a detailed description of the following dataset: UT-Zappos50K |
C-GQA | We propose a split built on top of Stanford GQA dataset originally proposed for VQA and name it Compositional GQA (C-GQA) dataset (see supplementary for the details). CGQA contains over 9.5k compositional labels making it the most extensive dataset for CZSL. With cleaner labels and a larger label space, our hope is tha... | Provide a detailed description of the following dataset: C-GQA |
Wind Speed Forecasting | Air pollution management through wind speed forecasting: the time series exhibits a daily cyclical behavior and a long-term seasonality. | Provide a detailed description of the following dataset: Wind Speed Forecasting |
Random Hierarchy Model | Artificial hierarchical datasets to study how neural networks learn hierarchical tasks. See papers for details. | Provide a detailed description of the following dataset: Random Hierarchy Model |
LSMI | # Large Scale Multi-Illuminant (LSMI) Dataset for Developing White Balance Algorithm under Mixed Illumination (ICCV 2021)
<!-- ABOUT THE PROJECT -->
## Change Log
**LSMI Dataset Version : 1.1**
1.0 : LSMI dataset released. (Aug 05, 2021)
1.1 : Add option for saving sub-pair images for 3-illuminant scene (e... | Provide a detailed description of the following dataset: LSMI |
EyePACS-light | This is a machine-learning-ready glaucoma dataset using a balanced subset of standardized fundus images from the Rotterdam EyePACS AIROGS train set. This dataset is split into training, validation, and test folders which contain 2500, 270, and 500 fundus images in each class respectively. Each training set has a folder... | Provide a detailed description of the following dataset: EyePACS-light |
SMDG | Standardized Multi-Channel Dataset for Glaucoma (SMDG-19) is a collection and standardization of 19 public datasets, comprised of full-fundus glaucoma images, associated image metadata like, optic disc segmentation, optic cup segmentation, blood vessel segmentation, and any provided per-instance text metadata like sex ... | Provide a detailed description of the following dataset: SMDG |
Small ImageNet 150 | This new dataset represents a subset of the ImageNet1k. It consists of 99000 images and 150 classes. 90000 of them are for training, 600 images for each class. The validation test size is 7500. For testing, we add 1500 images from the ImageNetV2 Top-Images dataset to the validation. | Provide a detailed description of the following dataset: Small ImageNet 150 |
EBD | A large-scale benchmark with 1605 high-resolution, well-annotated images, featuring more
complex scenes and a wider range of DOF settings. | Provide a detailed description of the following dataset: EBD |
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