Omkar2118/datasets huggingface dataset:
AViD

Is a collection of action videos from many different countries. The motivation is to create a public dataset that would benefit training and pretraining of action recognition models for everybody, rather than making it useful for limited countries.

Source: [AViD Dataset: Anonymized Videos from Diverse Countries](/paper/avid-dataset-anonymized-videos-from-diverse)

Introducing paper: AViD Dataset: Anonymized Videos from Diverse Countries
MTL-AQA

A new multitask action quality assessment (AQA) dataset, the largest to date, comprising of more than 1600 diving samples; contains detailed annotations for  fine-grained action recognition, commentary generation, and estimating the AQA score. Videos from multiple angles provided wherever available.

Source: [What and How Well You Performed? A Multitask Learning Approach to Action Quality Assessment](/paper/what-and-how-well-you-performed-a-multitask)

Introducing paper: What and How Well You Performed? A Multitask Learning Approach to Action Quality Assessment
AQA-7

Consists of 1106 action samples from seven actions with quality scores as measured by expert human judges.

Source: [Action Quality Assessment Across Multiple Actions](/paper/action-quality-assessment-across-multiple)

Introducing paper: Action Quality Assessment Across Multiple Actions
DocUNet
Full name: Document Image Unwarping via a Stacked U-Net

Various documents dataset.
Each of the 65 documents includes scanned ground truth images, both hard and easy distorted photos, and document-centered cropped images.

Image Source: [DocUNet: Document Image Unwarping via a Stacked U-Net](/paper/docunet-document-image-unwarping-via-a)

Introducing paper: DocUNet: Document Image Unwarping via a Stacked U-Net
AMZ Computers
Full name: amazon_electronics_computers

AMZ Computers is a co-purchase graph extracted from Amazon, where nodes represent products, edges represent the co-purchased relations of products, and features are bag-of-words vectors extracted from product reviews.
SVG-Icons8

A new large-scale dataset along with an open-source library for SVG manipulation.

Source: [DeepSVG: A Hierarchical Generative Network for Vector Graphics Animation](/paper/deepsvg-a-hierarchical-generative-network-for)

Introducing paper: DeepSVG: A Hierarchical Generative Network for Vector Graphics Animation
K2HPD

Includes 100K depth images under challenging scenarios.

Source: [Human Pose Estimation from Depth Images via Inference Embedded Multi-task Learning](/paper/human-pose-estimation-from-depth-images-via)

Introducing paper: Human Pose Estimation from Depth Images via Inference Embedded Multi-task Learning
Binarized MNIST

A binarized version of MNIST.

Source: [Binarized MNIST](http://www.dmi.usherb.ca/~larocheh/mlpython/_modules/datasets/binarized_mnist.html)
CAMO
Full name: Camouflaged Object

Camouflaged Object (CAMO) dataset specifically designed for the task of camouflaged object segmentation. We focus on two categories, i.e., naturally camouflaged objects and artificially camouflaged objects, which usually correspond to animals and humans in the real world, respectively. Camouflaged object images consists of 1250 images (1000 images for the training set and 250 images for the testing set). Non-camouflaged object images are collected from the MS-COCO dataset (1000 images for the training set and 250 images for the testing set). CAMO has objectness mask ground-truth.

Introducing paper: Anabranch Network for Camouflaged Object Segmentation
Hyperpartisan News Detection

Hyperpartisan News Detection was a dataset created for PAN @ SemEval 2019 Task 4. Given a news article text, decide whether it follows a hyperpartisan argumentation, i.e., whether it exhibits blind, prejudiced, or unreasoning allegiance to one party, faction, cause, or person.

There are two parts:

* byarticle: Labeled through crowdsourcing on an article basis. The data contains only articles for which a consensus among the crowdsourcing workers existed.
* bypublisher: Labeled by the overall bias of the publisher as provided by BuzzFeed journalists or MediaBiasFactCheck.com.
Tobacco-3482

The Tobacco-3482 dataset consists of document images belonging to 10 classes such as letter, form, email, resume, memo, etc. The dataset has 3482 images.
Skeleton-Mimetics

A dataset derived from the recently introduced Mimetics dataset.

Source: [Quo Vadis, Skeleton Action Recognition ?](/paper/quo-vadis-skeleton-action-recognition)

Introducing paper: Quo Vadis, Skeleton Action Recognition ?
UAVA
Full name: UAV Assistant

The UAVA,<i>UAV-Assistant</i>, dataset is specifically designed for fostering applications which consider UAVs and humans as cooperative agents.
We employ a real-world 3D scanned dataset (<a href="https://niessner.github.io/Matterport/">Matterport3D</a>), physically-based rendering, a gamiﬁed simulator for realistic drone navigation trajectory collection, to generate realistic multimodal data both from the user’s exocentric view of the drone, as well as the drone’s egocentric view.

Introducing paper: DronePose: Photorealistic UAV-Assistant Dataset Synthesis for 3D Pose Estimation via a Smooth Silhouette Loss
ContactPose

ContactPose is a dataset of hand-object contact paired with hand pose, object pose, and RGB-D images. ContactPose has 2306 unique grasps of 25 household objects grasped with 2 functional intents by 50 participants, and more than 2.9 M RGB-D grasp images. 

Source: [ContactPose: A Dataset of Grasps with Object Contact and Hand Pose](/paper/contactpose-a-dataset-of-grasps-with-object)

Introducing paper: ContactPose: A Dataset of Grasps with Object Contact and Hand Pose