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 601–610 of 1322 papers

Title	Date	Tasks	Status
ConViViT -- A Deep Neural Network Combining Convolutions and Factorized Self-Attention for Human Activity Recognition	Oct 22, 2023	Activity RecognitionHuman Activity Recognition	—Unverified
HAPRec: Hybrid Activity and Plan Recognizer	Apr 28, 2020	Action RecognitionActivity Recognition	—Unverified
Appearance Based Robot and Human Activity Recognition System	Feb 4, 2016	Activity RecognitionHuman Activity Recognition	—Unverified
HAR-DoReMi: Optimizing Data Mixture for Self-Supervised Human Activity Recognition Across Heterogeneous IMU Datasets	Mar 16, 2025	Activity RecognitionHuman Activity Recognition	—Unverified
Forward-Backward Greedy Algorithms for General Convex Smooth Functions over A Cardinality Constraint	Dec 31, 2013	Activity Recognitionfeature selection	—Unverified
A dataset for complex activity recognition withmicro and macro activities in a cooking scenario	Jun 18, 2020	Activity Recognition	—Unverified
Forensic Video Analytic Software	Sep 17, 2023	Activity RecognitionAnomaly Detection	—Unverified
Follow the Attention: Combining Partial Pose and Object Motion for Fine-Grained Action Detection	May 11, 2019	Action DetectionActivity Detection	—Unverified
Creating a Large-scale Synthetic Dataset for Human Activity Recognition	Jul 21, 2020	Activity RecognitionHuman Activity Recognition	—Unverified
An Unsupervised Approach for Automatic Activity Recognition based on Hidden Markov Model Regression	Dec 25, 2013	Activity RecognitionGeneral Classification	—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