19,997 machine learning datasets
19,997 dataset results
KnowIT VQA is a video dataset with 24,282 human-generated question-answer pairs about The Big Bang Theory. The dataset combines visual, textual and temporal coherence reasoning together with knowledge-based questions, which need of the experience obtained from the viewing of the series to be answered.
LoDoPaB-CT is a dataset of computed tomography images and simulated low-dose measurements. It contains over 40,000 scan slices from around 800 patients selected from the LIDC/IDRI Database.
A logo detection dataset with full annotation, which has 3,000 logo categories, about 200,000 manually annotated logo objects and 158,652 images. LogoDet-3K creates a more challenging benchmark for logo detection, for its higher comprehensive coverage and wider variety in both logo categories and annotated objects compared with existing datasets.
MEIR is a substantially challenging dataset over that which has been previously available to support research into image repurposing detection. The new dataset includes location, person, and organization manipulations on real-world data sourced from Flickr.
MSASL is a real-life large-scale sign language data set comprising over 25,000 annotated videos.
Presents two high-quality large-scale CLS datasets based on existing monolingual summarization datasets.
Presents half a million samples and structured meta-data to encourage further research and societal engagement.
PathTrack is a dataset for person tracking which contains more than 15,000 person trajectories in 720 sequences.
A novel large-scale multi-domain dataset for persona-based empathetic conversations.
PTB-TIR is a Thermal InfraRed (TIR) pedestrian tracking benchmark, which provides 60 TIR sequences with mannuly annoations. The benchmark is used to fair evaluate TIR trackers.
Consists of 330,000 sketches and 204,000 photos spanning across 110 categories.
RAVEN-FAIR is a modified version of the RAVEN dataset.
A human-curated ChineseReading Comprehension dataset on Opinion. The questions in ReCO are opinion based queries issued to the commercial search engine. The passages are provided by the crowdworkers who extract the support snippet from the retrieved documents.
ReDWeb-S is a large-scale challenging dataset for Salient Object Detection. It has totally 3179 images with various real-world scenes and high-quality depth maps. The dataset is split into a training set with 2179 RGB-D image pairs and a testing set with the remaining 1000 image pairs.
SelQA is a dataset that consists of questions generated through crowdsourcing and sentence length answers that are drawn from the ten most prevalent topics in the English Wikipedia.
A new dataset called SOBA, named after Shadow-OBject Association, with 3,623 pairs of shadow and object instances in 1,000 photos, each with individual labeled masks.
SPEECH-COCO contains speech captions that are generated using text-to-speech (TTS) synthesis resulting in 616,767 spoken captions (more than 600h) paired with images.
Provides four new test sets for the Stanford Question Answering Dataset (SQuAD) and evaluate the ability of question-answering systems to generalize to new data.
The Standardized Project Gutenberg Corpus (SPGC) is an open science approach to a curated version of the complete PG data containing more than 50,000 books and more than 3×109 word-tokens.
Tunisian Sentiment Analysis Corpus (TSAC) is a Tunisian Dialect corpus of 17.000 comments from Facebook.