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 861–870 of 1322 papers

Title	Date	Tasks	Status
A Framework of Combining Short-Term Spatial/Frequency Feature Extraction and Long-Term IndRNN for Activity Recognition	Nov 1, 2020	Activity RecognitionHuman Activity Recognition	—Unverified
Inference for Change Points in High Dimensional Mean Shift Models	Jul 19, 2021	Activity Recognitionvalid	—Unverified
Information We Can Extract About a User From 'One Minute Mobile Application Usage'	Jul 27, 2022	Activity Recognition	—Unverified
Informed Democracy: Voting-based Novelty Detection for Action Recognition	Oct 30, 2018	Action ClassificationAction Recognition	—Unverified
Initial Findings on Sensor based Open Vocabulary Activity Recognition via Text Embedding Inversion	Jan 13, 2025	Activity RecognitionDescriptive	—Unverified
Initial Investigation of Kolmogorov-Arnold Networks (KANs) as Feature Extractors for IMU Based Human Activity Recognition	Jun 16, 2024	Activity RecognitionHuman Activity Recognition	—Unverified
InMyFace: Inertial and Mechanomyography-Based Sensor Fusion for Wearable Facial Activity Recognition	Feb 8, 2023	Activity RecognitionSensor Fusion	—Unverified
In-sensor 24 classes HAR under 850 Bytes	Feb 13, 2025	Activity RecognitionHuman Activity Recognition	—Unverified
In Shift and In Variance: Assessing the Robustness of HAR Deep Learning Models against Variability	Mar 14, 2025	Activity RecognitionDisease Prediction	—Unverified
From Lab to Field: Real-World Evaluation of an AI-Driven Smart Video Solution to Enhance Community Safety	Dec 4, 2023	Activity RecognitionAnomaly Detection	—Unverified

Show:10 25 50

← PrevPage 87 of 133Next →

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