Omkar2118/datasets huggingface dataset:
ETH Py150 Open

A massive, deduplicated corpus of 7.4M Python files from GitHub.

Source: [Learning and Evaluating Contextual Embedding of Source Code](/paper/pre-trained-contextual-embedding-of-source-1)

Introducing paper: Learning and Evaluating Contextual Embedding of Source Code
ETH-XGaze

Consists of over one million high-resolution images of varying gaze under extreme head poses. The dataset is collected from 110 participants with a custom hardware setup including 18 digital SLR cameras and adjustable illumination conditions, and a calibrated system to record ground truth gaze targets. 

Source: [ETH-XGaze: A Large Scale Dataset for Gaze Estimation under Extreme Head Pose and Gaze Variation](/paper/eth-xgaze-a-large-scale-dataset-for-gaze)

Official competition on Codalab: [https://competitions.codalab.org/competitions/28930](https://competitions.codalab.org/competitions/28930)

Introducing paper: ETH-XGaze: A Large Scale Dataset for Gaze Estimation under Extreme Head Pose and Gaze Variation
eTRIMS Image Database

The database is comprised of two datasets, the 4-Class eTRIMS Dataset with 4 annotated object classes and the 8-Class eTRIMS Dataset with 8 annotated object classes.

Source: [eTRIMS Image Database](http://www.ipb.uni-bonn.de/projects/etrims_db/)
ETT
Full name: Electricity Transformer Temperature

The **Electricity Transformer Temperature** (**ETT**) is a crucial indicator in the electric power long-term deployment. This dataset consists of 2 years data from two separated counties in China. To explore the granularity on the Long sequence time-series forecasting (LSTF) problem, different subsets are created, {ETTh1, ETTh2} for 1-hour-level and ETTm1 for 15-minutes-level. Each data point consists of the target value ”oil temperature” and 6 power load features. The train/val/test is 12/4/4 months.

Source: [https://arxiv.org/pdf/2012.07436.pdf](https://arxiv.org/pdf/2012.07436.pdf)
Image Source: [https://github.com/zhouhaoyi/ETDataset](https://github.com/zhouhaoyi/ETDataset)

Introducing paper: Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting
EuroCity Persons

The EuroCity Persons dataset provides a large number of highly diverse, accurate and detailed annotations of pedestrians, cyclists and other riders in urban traffic scenes. The images for this dataset were collected on-board a moving vehicle in 31 cities of 12 European countries. With over 238,200 person instances manually labeled in over 47,300 images, EuroCity Persons is nearly one order of magnitude larger than person datasets used previously for benchmarking. The dataset furthermore contains a large number of person orientation annotations (over 211,200).

Introducing paper: The EuroCity Persons Dataset: A Novel Benchmark for Object Detection
Europarl ConcoDisco Dataset

The ConcoDisco Corpus is an English-French parallel corpus with discourse relations (DRs) and discourse connectives (DCs) annotations.

Source: [https://github.com/mjlaali/Europarl-ConcoDisco](https://github.com/mjlaali/Europarl-ConcoDisco)
Image Source: [https://github.com/mjlaali/Europarl-ConcoDisco](https://github.com/mjlaali/Europarl-ConcoDisco)

Introducing paper: Improving Discourse Relation Projection to Build Discourse Annotated Corpora
Europeana Newspapers

Europeana Newspapers consists of four datasets with 100 pages each for the languages Dutch, French, German (including Austrian) as part of the Europeana Newspapers project is expected to contribute to the further development and improvement of named entity recognition systems with a focus on historical content.

Source: [An Open Corpus for Named Entity Recognition in Historic Newspapers](/paper/an-open-corpus-for-named-entity-recognition)

Introducing paper: An Open Corpus for Named Entity Recognition in Historic Newspapers
European Flood 2013 Dataset

This dataset consists of 3,710 flood images, annotated by domain experts regarding their relevance with respect to three tasks (determining the flooded area, inundation depth, water pollution).

Source: [https://github.com/cvjena/eu-flood-dataset](https://github.com/cvjena/eu-flood-dataset)
Image Source: [https://github.com/cvjena/eu-flood-dataset](https://github.com/cvjena/eu-flood-dataset)

Introducing paper: Enhancing Flood Impact Analysis using Interactive Retrieval of Social Media Images
Event-focused Emotion Corpora for German and English

A corpus designed in analogy to the well-established English ISEAR emotion dataset.

Source: [Crowdsourcing and Validating Event-focused Emotion Corpora for German and English](/paper/crowdsourcing-and-validating-event-focused)

Introducing paper: Crowdsourcing and Validating Event-focused Emotion Corpora for German and English
EventKG+Click

Builds upon the event-centric EventKG knowledge graph and language-specific information on user interactions with events, entities, and their relations derived from the Wikipedia clickstream.

Source: [EventKG+Click: A Dataset of Language-specific Event-centric User Interaction Traces](/paper/eventkg-click-a-dataset-of-language-specific)

Introducing paper: EventKG+Click: A Dataset of Language-specific Event-centric User Interaction Traces
Event-QA

Contains 1000 semantic queries and the corresponding English, German and Portuguese verbalizations for EventKG - an event-centric knowledge graph with more than 970 thousand events.

Source: [Event-QA: A Dataset for Event-Centric Question Answering over Knowledge Graphs](/paper/event-qa-a-dataset-for-event-centric-question)

Introducing paper: Event-QA: A Dataset for Event-Centric Question Answering over Knowledge Graphs
EV-IMO

Includes accurate pixel-wise motion masks, egomotion and ground truth depth. 

Source: [EV-IMO: Motion Segmentation Dataset and Learning Pipeline for Event Cameras](/paper/ev-imo-motion-segmentation-dataset-and)

Introducing paper: EV-IMO: Motion Segmentation Dataset and Learning Pipeline for Event Cameras
EXAMS

A new benchmark dataset for cross-lingual and multilingual question answering for high school examinations. Collects more than 24,000 high-quality high school exam questions in 16 languages, covering 8 language families and 24 school subjects from Natural Sciences and Social Sciences, among others. EXAMS offers a fine-grained evaluation framework across multiple languages and subjects, which allows precise analysis and comparison of various models. 

Source: [EXAMS: A Multi-Subject High School Examinations Dataset for Cross-Lingual and Multilingual Question Answering](/paper/exams-a-multi-subject-high-school)

Introducing paper: EXAMS: A Multi-Subject High School Examinations Dataset for Cross-Lingual and Multilingual Question Answering
ExDark
Full name: Exclusively Dark Image Dataset

The **Exclusively Dark** (ExDARK) dataset is a collection of 7,363 low-light images from very low-light environments to twilight (i.e 10 different conditions) with 12 object classes (similar to PASCAL VOC) annotated on both image class level and local object bounding boxes.

Source: [https://github.com/cs-chan/Exclusively-Dark-Image-Dataset](https://github.com/cs-chan/Exclusively-Dark-Image-Dataset)

Introducing paper: Getting to Know Low-light Images with The Exclusively Dark Dataset
EXEQ-300k

The **EXEQ-300k** dataset contains 290,479 detailed questions with corresponding math headlines from Mathematics Stack Exchange. The dataset can be used to generate concise math headlines from detailed math questions.

Source: [https://arxiv.org/pdf/1912.00839.pdf](https://arxiv.org/pdf/1912.00839.pdf)

Introducing paper: Automatic Generation of Headlines for Online Math Questions
Explainable Abstract Trains

An image dataset containing simplified representations of trains. It aims to provide a platform for the application and research of algorithms for justification and explanation extraction. The dataset is accompanied by an ontology that conceptualizes and classifies the depicted trains based on their visual characteristics, allowing for a precise understanding of how each train was labeled. Each image in the dataset is annotated with multiple attributes describing the trains' features and with bounding boxes for the train elements. 

Source: [Explainable Abstract Trains Dataset](/paper/explainable-abstract-trains-dataset)

Introducing paper: Explainable Abstract Trains Dataset
ExPose
Full name: EXpressive POse and Shape rEgression

Curates a dataset of SMPL-X fits on in-the-wild images.

Source: [Monocular Expressive Body Regression through Body-Driven Attention](/paper/monocular-expressive-body-regression-through)

Introducing paper: Monocular Expressive Body Regression through Body-Driven Attention
EyeQ

Dataset with 28,792 retinal images from the EyePACS dataset, based on a three-level quality grading system (i.e., `Good', `Usable' and `Reject') for evaluating RIQA methods. 

Source: [Evaluation of Retinal Image Quality Assessment Networks in Different Color-spaces](/paper/evaluation-of-retinal-image-quality)

Introducing paper: Evaluation of Retinal Image Quality Assessment Networks in Different Color-spaces
Facebook Post Reactions

Collects posts (and their reactions) from Facebook pages of large supermarket chains.

Source: [Social Emotion Mining Techniques for Facebook Posts Reaction Prediction](/paper/social-emotion-mining-techniques-for-facebook)

Introducing paper: Social Emotion Mining Techniques for Facebook Posts Reaction Prediction