Omkar2118/datasets huggingface dataset:
EPIC-Hotspot

From Grounded Human-Object Interaction Hotspots from Video (ICCV'19): We collect annotations for interaction keypoints on EPIC Kitchens in order to quantitatively evaluate our method in parallel to the OPRA dataset (where annotations are available). We note that these annotations are collected purely for evaluation, and are not used for training our model. We select the 20 most frequent verbs, and select 31 nouns that afford these interactions.

Introducing paper: Grounded Human-Object Interaction Hotspots from Video
Ranking social media news feed

A dataset consisting of recipient 46 users and, 26180 tweets. The dataset includes the news feed of the users and 13 features that may influence the relevance of the tweets.

Introducing paper: Ranking Social Media News Feeds: A Comparative Study of Personalized and Non-personalized Prediction Models
NIH-CXR-LT
Full name: Long-tailed (LT) NIH ChestXRay14

NIH-CXR-LT. NIH ChestXRay14 contains over 100,000 chest X-rays labeled with 14 pathologies, plus a “No Findings” class. We construct a single-label, long-tailed version of the NIH ChestXRay14 dataset by introducing five new disease findings described above. The resulting NIH-CXR-LT dataset has 20 classes, including 7 head classes, 10 medium classes, and 3 tail classes. NIH-CXR-LT contains 88,637 images labeled with one of 19 thorax diseases, with 68,058 training and 20,279 test images. The validation and balanced test sets contain 15 and 30 images per class, respectively.

Introducing paper: Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study
MIMIC-CXR-LT
Full name: long-tailed version of MIMIC-CXR

MIMIC-CXR-LT. We construct a single-label, long-tailed version of MIMIC-CXR in a similar manner. MIMIC-CXR is a multi-label classification dataset with over 200,000 chest X-rays labeled with 13 pathologies and a “No Findings” class. The resulting MIMIC-CXR-LT dataset contains 19 classes, of which 10 are head classes, 6 are medium classes, and 3 are tail classes. MIMIC-CXR-LT contains 111,792 images labeled with one of 18 diseases, with 87,493 training images and 23,550 test set images. The validation and balanced test sets contain 15 and 30 images per class, respectively.

Introducing paper: Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study