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 401–410 of 1322 papers

Title	Date	Tasks	Status
A Wireless-Vision Dataset for Privacy Preserving Human Activity Recognition	May 24, 2022	Action SegmentationActivity Recognition	—Unverified
A Wi-Fi Signal-Based Human Activity Recognition Using High-Dimensional Factor Models	Nov 10, 2023	Activity RecognitionHuman Activity Recognition	—Unverified
A MIMO Radar-Based Metric Learning Approach for Activity Recognition	Nov 2, 2021	Activity RecognitionFew-Shot Learning	—Unverified
Domain Generalization through Audio-Visual Relative Norm Alignment in First Person Action Recognition	Oct 19, 2021	Action RecognitionActivity Recognition	—Unverified
A Wearable Multi-Modal Edge-Computing System for Real-Time Kitchen Activity Recognition	Sep 10, 2024	Activity RecognitionEdge-computing	—Unverified
Domain Generalization for Activity Recognition via Adaptive Feature Fusion	Jul 21, 2022	Activity RecognitionDomain Adaptation	—Unverified
Domain-Adversarial Anatomical Graph Networks for Cross-User Human Activity Recognition	May 8, 2025	Activity RecognitionDomain Generalization	—Unverified
AVD: Adversarial Video Distillation	Jul 12, 2019	Activity RecognitionDecoder	—Unverified
Am I fit for this physical activity? Neural embedding of physical conditioning from inertial sensors	Mar 22, 2021	Activity RecognitionHuman Activity Recognition	—Unverified
Domain Adaptation for Inertial Measurement Unit-based Human Activity Recognition: A Survey	Apr 7, 2023	Activity RecognitionDomain Adaptation	—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