Omkar2118/datasets huggingface dataset:
OMG-Emotion
Full name: One-Minute Gradual-Emotional Behavior

The One-Minute Gradual-Emotional Behavior dataset (**OMG-Emotion**) dataset is composed of Youtube videos which are around a minute in length and are annotated taking into consideration a continuous emotional behavior. The videos were selected using a crawler technique that uses specific keywords based on long-term emotional behaviors such as "monologues", "auditions", "dialogues" and "emotional scenes".

It contains 567 emotion videos with an average length of 1 minute, collected from a variety of Youtube channels. The videos were separated into clips based on utterances, and each utterance was annotated by at least five independent subjects using the Amazon Mechanical Turk tool.

Introducing paper: The OMG-Emotion Behavior Dataset
KinGaitWild
Full name: Kinship verification from gait dataset

To study kinship verification from gait, we collected the dataset KinGaitWild consisting of several videos from youtube. Most of the videos were taken under uncontrolled conditions in terms of background, camera motion, luminance and viewpoints. The KinGaitWild dataset contains 105 videos of celebrities and their relatives. The average time duration of each video is around 10 seconds. The database includes 60 pairs of Father-Son (FS) relationships. These pairs are equally split into 5 groups. We focus in this study on the Father-Son relationships.
The database collection was done as follows. First, we used the YouTube Data API to search for videos showing celebrities walking in the wild. To avoid biases, we selected
the pairs of celebrities so that the videos are not originated from the same source nor environment. For each video, we labeled the position of each specified person by a bounding box (bbox). These bboxes are used to estimate the human pose for silhouette-based approaches and to crop the region of interest for both the video-based and deep-learning-based approaches.
FINO-Net

**FINO-Net** is a multimodal (RGB, depth and audio) dataset, containing 229 real-world manipulation data of 5 different manipulation types recorded with a Baxter robot.

Introducing paper: FINO-Net: A Deep Multimodal Sensor Fusion Framework for Manipulation Failure Detection
CoronaVis

**CoronaVis** is a dataset of tweets related to coronavirus.

Introducing paper: CoronaVis: A Real-time COVID-19 Tweets Analyzer
Multi-Codec DASH

This is a multi-codec DASH dataset comprising AVC, HEVC, VP9, and AV1 in order to enable interoperability testing and streaming experiments for the efficient usage of these codecs under various conditions.

Introducing paper: Multi-Codec DASH Dataset
UCR Time Series Classification Archive
Full name: UCR Time Series Classification Archive

The UCR Time Series Archive - introduced in 2002,
has become an important resource in the time series data mining
community, with at least one thousand published papers making
use of at least one data set from the archive. The original
incarnation of the archive had sixteen data sets but since that
time, it has gone through periodic expansions. The last expansion
took place in the summer of 2015 when the archive grew from
45 to 85 data sets. This paper introduces and will focus on the
new data expansion from 85 to 128 data sets. Beyond expanding
this valuable resource, this paper offers pragmatic advice to
anyone who may wish to evaluate a new algorithm on the archive.
Finally, this paper makes a novel and yet actionable claim: of the
hundreds of papers that show an improvement over the standard
baseline (1-nearest neighbor classification), a large fraction may
be misattributing the reasons for their improvement. Moreover,
they may have been able to achieve the same improvement with
a much simpler modification, requiring just a single line of code.

Introducing paper: The UCR Time Series Archive
YoutubeGraph-Dyn

YoutubeGraph-Dyn is an evolving graph dataset generated from YouTube real-world interactions. It can be used to study temporal evolution on graphs. YoutubeGraph-Dyn provides intra-day time granularity (with 416 snapshots taken every 6 hours for a period of 104 days), multi-modal relationships that capture different aspects of the data, multiple attributes including timestamped, non-timestamped, word embeddings, and integers.

Introducing paper: Tracking Temporal Evolution of Graphs using Non-Timestamped Data
HoMG

HoMG is a holoscopic 3D micro-gesture dataset captured with a holoscopic 3D camera. HoMG database recorded the image sequence of 3 conventional gestures from 40 participants under different settings and conditions. For the purpose of H3D micro-gesture recognition, HoMG has a video subset of 960 videos and a still image subset with 30,635 images.

Introducing paper: Holoscopic 3D Micro-Gesture Database for Wearable Device Interaction
Wildtrack

Wildtrack is a large-scale and high-resolution dataset. It has been captured with seven static cameras in a public open area, and unscripted dense groups of pedestrians standing and walking. Together with the camera frames, we provide an accurate joint (extrinsic and intrinsic) calibration, as well as 7 series of 400 annotated
frames for detection at a rate of 2 frames per second. This results in over 40 000 bounding boxes delimiting every person present in the area of interest, for a total of more than
300 individuals.

Introducing paper: WILDTRACK: A Multi-Camera HD Dataset for Dense Unscripted Pedestrian Detection
pixraw10P
Full name: pixraw10P

face image datasets

Introducing paper: Feature Selection: A Data Perspective
warpPIE10P
Full name: warpPIE10P

face dataset

Introducing paper: Ensemble Learning for Spectral Clustering
iris
Full name: iris

The Iris flower data set or Fisher's Iris data set is a multivariate data set introduced by the British statistician, eugenicist, and biologist Ronald Fisher in his 1936 paper The use of multiple measurements in taxonomic problems as an example of linear discriminant analysis. It is sometimes called Anderson's Iris data set because Edgar Anderson collected the data to quantify the morphologic variation of Iris flowers of three related species. Two of the three species were collected in the Gaspé Peninsula "all from the same pasture, and picked on the same day and measured at the same time by the same person with the same apparatus".

Introducing paper: Ensemble Learning for Spectral Clustering