Activity Recognition

Human Activity Recognition is the problem of identifying events performed by humans given a video input. It is formulated as a binary (or multiclass) classification problem of outputting activity class labels. Activity Recognition is an important problem with many societal applications including smart surveillance, video search/retrieval, intelligent robots, and other monitoring systems.

Source: Learning Latent Sub-events in Activity Videos Using Temporal Attention Filters

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 631–640 of 1322 papers

Title	Date	Tasks	Status
Cross-user activity recognition via temporal relation optimal transport	Mar 12, 2024	Activity RecognitionDomain Adaptation	—Unverified
Human Activity Recognition for Edge Devices	Mar 18, 2019	Activity RecognitionHuman Activity Recognition	—Unverified
Human Activity Recognition for Mobile Robot	Jan 23, 2018	Activity RecognitionHuman Activity Recognition	—Unverified
Human activity recognition from mobile inertial sensors using recurrence plots	Dec 5, 2017	Activity RecognitionGeneral Classification	—Unverified
CSI-Based Cross-Domain Activity Recognition via Zero-Shot Prototypical Networks	Dec 12, 2023	Activity RecognitionCross-Domain Activity Recognition	—Unverified
An Unsupervised Approach for Automatic Activity Recognition based on Hidden Markov Model Regression	Dec 25, 2013	Activity RecognitionGeneral Classification	—Unverified
Human Activity Recognition from Wi-Fi CSI Data Using Principal Component-Based Wavelet CNN	Dec 26, 2022	Activity RecognitionHuman Activity Recognition	—Unverified
CSI-Based Efficient Self-Quarantine Monitoring System Using Branchy Convolution Neural Network	May 24, 2023	Activity RecognitionHuman Activity Recognition	—Unverified
ActionNet-VE Dataset: A Dataset for Describing Visual Events by Extending VIRAT Ground 2.0	Nov 25, 2015	Activity RecognitionHuman Activity Recognition	—Unverified
Human Activity Recognition on wrist-worn accelerometers using self-supervised neural networks	Dec 22, 2021	Activity RecognitionHuman Activity Recognition	—Unverified

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All datasets RWF-2000 Stanford40 First-Person Hand Action Benchmark Self-stimulatory Behavior Dataset

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Structured Keypoint Pooling	Accuracy	93.4	—	Unverified
2	Semi-Supervised Hard Attention (SSHA); pretrained on Deepmind Kinetics dataset	Accuracy	90.4	—	Unverified
3	Human Skeletons + Change Detection	Accuracy	90.25	—	Unverified
4	Separable Convolutional LSTM	Accuracy	89.75	—	Unverified
5	SPIL Convolution	Accuracy	89.3	—	Unverified
6	Flow Gated Network	Accuracy	87.25	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FocusCLIP	Top-3 Accuracy (%)	10.47	—	Unverified
2	CLIP	Top-3 Accuracy (%)	6.49	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Boutaleb et al.	1:1 Accuracy	97.91	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	all-landmark-model	Activity Recognition	0.76	—	Unverified