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 1061–1070 of 1322 papers

Title	Date	Tasks	Status
A Heat-Map-based Algorithm for Recognizing Group Activities in Videos	Feb 21, 2015	Activity RecognitionGroup Activity Recognition	—Unverified
A Hybrid Framework for Action Recognition in Low-Quality Video Sequences	Mar 11, 2019	Action RecognitionActivity Recognition	—Unverified
AI-Powered Non-Contact In-Home Gait Monitoring and Activity Recognition System Based on mm-Wave FMCW Radar and Cloud Computing	Aug 11, 2022	Activity RecognitionCloud Computing	—Unverified
A Lightweight Deep Learning Model for Human Activity Recognition on Edge Devices	Sep 20, 2019	Activity RecognitionDeep Learning	—Unverified
A Logic Programming Approach to Activity Recognition	May 28, 2009	Activity Recognition	—Unverified
A Masked Semi-Supervised Learning Approach for Otago Micro Labels Recognition	May 21, 2024	Activity RecognitionHuman Activity Recognition	—Unverified
Maximum Likelihood Speed Estimation of Moving Objects in Video Signals	Mar 10, 2020	Activity RecognitionHuman Activity Recognition	—Unverified
"Filling the Blanks'': Identifying Micro-activities that Compose Complex Human Activities of Daily Living	Jun 22, 2023	Activity RecognitionAttribute	—Unverified
Am I fit for this physical activity? Neural embedding of physical conditioning from inertial sensors	Mar 22, 2021	Activity RecognitionHuman Activity Recognition	—Unverified
A MIMO Radar-Based Metric Learning Approach for Activity Recognition	Nov 2, 2021	Activity RecognitionFew-Shot Learning	—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