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Datasets/SBU / SBU-Refine

SBU / SBU-Refine

SBU-Kinect-Interaction dataset v2.0

ActionsRGB-DIntroduced 2019-11-12

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.

	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

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.

Benchmarks

16k/Balanced Error Rate2D Classification/Balanced Error Rate2D Object Detection/Balanced Error Rate3D/Balanced Error Rate3D Action Recognition/AccuracyAction Detection/AccuracyAction Localization/AccuracyAction Recognition/AccuracyActivity Recognition/AccuracyHuman Interaction Recognition/AccuracyObject Detection/Balanced Error RateRGB Salient Object Detection/Balanced Error RateShadow Detection/BERTemporal Action Localization/AccuracyVideo/AccuracyZero-Shot Learning/Accuracy

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Papers
28
Benchmarks
16

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Tasks

16k2D Classification2D Object Detection3D3D Action RecognitionAction DetectionAction LocalizationAction RecognitionActivity RecognitionHuman Interaction RecognitionObject DetectionRGB Salient Object DetectionShadow DetectionSkeleton Based Action RecognitionTemporal Action LocalizationVideoZero-Shot Learning