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 1051–1060 of 1322 papers

Title	Date	Tasks	Status
Poselet Key-Framing: A Model for Human Activity Recognition	Jun 1, 2013	Activity RecognitionHuman Activity Recognition	—Unverified
PosePilot: An Edge-AI Solution for Posture Correction in Physical Exercises	May 25, 2025	Activity RecognitionComputational Efficiency	—Unverified
Pose Uncertainty Aware Movement Synchrony Estimation via Spatial-Temporal Graph Transformer	Aug 1, 2022	Activity RecognitionContrastive Learning	—Unverified
Post-training Iterative Hierarchical Data Augmentation for Deep Networks	Dec 1, 2020	Activity RecognitionData Augmentation	—Unverified
Pragmatic classification of movement primitives for stroke rehabilitation	Feb 22, 2019	Activity RecognitionClassification	—Unverified
Predicting Human Depression with Hybrid Data Acquisition utilizing Physical Activity Sensing and Social Media Feeds	May 28, 2025	Activity RecognitionSentiment Analysis	—Unverified
Predicting User-specific Future Activities using LSTM-based Multi-label Classification	Nov 6, 2022	Activity PredictionActivity Recognition	—Unverified
PresSim: An End-to-end Framework for Dynamic Ground Pressure Profile Generation from Monocular Videos Using Physics-based 3D Simulation	Feb 1, 2023	Activity RecognitionHuman Activity Recognition	—Unverified
PressureTransferNet: Human Attribute Guided Dynamic Ground Pressure Profile Transfer using 3D simulated Pressure Maps	Aug 1, 2023	Activity RecognitionAnomaly Detection	—Unverified
Privacy in Multimodal Federated Human Activity Recognition	May 20, 2023	Activity RecognitionFederated Learning	—Unverified

Show:10 25 50

← PrevPage 106 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