Omkar2118/datasets huggingface dataset:
EgoSchema

**EgoSchema** is very long-form video question-answering dataset, and benchmark to evaluate long video understanding capabilities of modern vision and language systems. Derived from Ego4D, EgoSchema consists of over 5000 human curated multiple choice question answer pairs, spanning over 250 hours of real video data, covering a very broad range of natural human activity and behavior.
Spatial LibriSpeech

**Spatial LibriSpeech** is spatial audio dataset with over 650 hours of 19-channel audio, first-order ambisonics, and optional distractor noise. Spatial LibriSpeech is designed for machine learning model training, and it includes labels for source position, speaking direction, room acoustics and geometry.

Introducing paper: Spatial LibriSpeech: An Augmented Dataset for Spatial Audio Learning
NIH 3T3 microtubule cell dataset

The data consists of 21 images of microtubules in PFA-fixed NIH 3T3 mouse embryonic fibroblasts (DSMZ: ACC59) labeled with a mouse anti-alpha-tubulin monoclonal IgG1 antibody (Thermofisher A11126, primary antibody) and visualized by a blue-fluorescent Alexa Fluor 405 goat anti-mouse IgG antibody (Thermofisher A-31553, secondary antibody). Acquisition of the images was performed using a confocal microscope (Olympus IX81).

The images feature cell clusters of various sizes at various scales and densities, with no underlying cluster assignment.

The images belong to Ulrike Rölleke and Sarah Köster (University of Göttingen).

Introducing paper: A scalable clustering algorithm to approximate graph cuts