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 1091–1100 of 1322 papers

Title	Date	Tasks	Status
Anonymizing Egocentric Videos	Jan 1, 2021	Activity Recognitionobject-detection	—Unverified
A Novel Indoor Positioning System for unprepared firefighting scenarios	Aug 4, 2020	Activity RecognitionOptical Flow Estimation	—Unverified
A Novel Multi-Stage Training Approach for Human Activity Recognition from Multimodal Wearable Sensor Data Using Deep Neural Network	Jan 3, 2021	Activity RecognitionHuman Activity Recognition	—Unverified
A Novel Two Stream Decision Level Fusion of Vision and Inertial Sensors Data for Automatic Multimodal Human Activity Recognition System	Jun 27, 2023	Activity RecognitionHuman Activity Recognition	—Unverified
An Overview of Human Activity Recognition Using Wearable Sensors: Healthcare and Artificial Intelligence	Mar 29, 2021	Activity RecognitionFeature Engineering	—Unverified
An Overview of Violence Detection Techniques: Current Challenges and Future Directions	Sep 21, 2022	Activity Recognition	—Unverified
Answering Image Riddles using Vision and Reasoning through Probabilistic Soft Logic	Nov 17, 2016	Activity RecognitionQuestion Answering	—Unverified
An Unsupervised Approach for Automatic Activity Recognition based on Hidden Markov Model Regression	Dec 25, 2013	Activity RecognitionGeneral Classification	—Unverified
Appearance Based Robot and Human Activity Recognition System	Feb 4, 2016	Activity RecognitionHuman Activity Recognition	—Unverified
Application of Machine Learning Techniques in Human Activity Recognition	Oct 19, 2015	Action DetectionActivity Detection	—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