Omkar2118/datasets huggingface dataset:
N-UCLA
Full name: Northwestern-UCLA Multiview Action 3D Dataset

The Multiview 3D event dataset is capture by me and Xiaohan Nie in UCLA. it contains RGB, depth and human skeleton data captured simultaneously by three Kinect cameras. This dataset include 10 action categories: pick up with one hand, pick up with two hands, drop trash, walk around, sit down, stand up, donning, doffing, throw, carry. Each action is performed by 10 actors. This dataset contains data taken from a variety of viewpoints.
The dataset can be found in part-1, part-2 part-3, part-4, part-5, part-6, part-7, part-8, part-9, part-10, part-11, part-12, part-13, part-14, part-15, part-16,
We also created a version of the dataset that only contains RGB videos: RGB videos only.
SBU / SBU-Refine
Full name: SBU-Kinect-Interaction dataset v2.0

**SBU-Kinect-Interaction dataset version 2.0** comprises of RGB-D video sequences of humans performing interaction activities that are recording using the Microsoft Kinect sensor. This dataset was originally recorded for a class project, and it must be used only for the purposes of research. If you use this dataset in your work, please cite the following paper.
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	Kiwon Yun, Jean Honorio, Debaleena Chattopadhyay, Tamara L. Berg, and Dimitris Samaras, The 2nd International Workshop on Human Activity Understanding from 3D Data at Conference on Computer Vision and Pattern Recognition (HAU3D-CVPRW), CVPR 2012
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SBU-Refine: SBU-Refine relabels the test set manually and refines the noise labels in training set by algorithm. H. Yang, T. Wang, X. Hu, and C.-W. Fu, “SILT: Shadow-aware iterative label tuning for learning to detect shadows from noisy labels,” in ICCV, 2023, pp. 12 687–12 698.
Acted Facial Expressions In The Wild (AFEW)

Acted Facial Expressions In The Wild (AFEW) is a dynamic temporal facial expressions data corpus consisting of close to real world environment extracted from movie