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

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Showing 1021–1030 of 1322 papers

Title	Date	Tasks	Status
Optical Flow Estimation in 360^ Videos: Dataset, Model and Application	Jan 27, 2023	Activity RecognitionEgocentric Activity Recognition	—Unverified
Optimised Convolutional Neural Networks for Heart Rate Estimation and Human Activity Recognition in Wrist Worn Sensing Applications	Mar 30, 2020	Activity RecognitionHeart rate estimation	—Unverified
Optimized Gated Deep Learning Architectures for Sensor Fusion	Oct 8, 2018	Activity RecognitionAutonomous Driving	—Unverified
Ordered Atomic Activity for Fine-grained Interactive Traffic Scenario Understanding	Jan 1, 2023	Activity Recognition	—Unverified
Order Matters: On Parameter-Efficient Image-to-Video Probing for Recognizing Nearly Symmetric Actions	Mar 31, 2025	Activity Recognition	—Unverified
Otago Exercises Monitoring for Older Adults by a Single IMU and Hierarchical Machine Learning Models	Oct 5, 2023	Activity RecognitionHuman Activity Recognition	—Unverified
Overview of Human Activity Recognition Using Sensor Data	Sep 12, 2023	Activity RecognitionDeep Learning	—Unverified
OV-HHIR: Open Vocabulary Human Interaction Recognition Using Cross-modal Integration of Large Language Models	Dec 31, 2024	Activity RecognitionHuman Interaction Recognition	—Unverified
P2LHAP:Wearable sensor-based human activity recognition, segmentation and forecast through Patch-to-Label Seq2Seq Transformer	Mar 13, 2024	Activity RecognitionAll	—Unverified
PALMAR: Towards Adaptive Multi-inhabitant Activity Recognition in Point-Cloud Technology	Jun 22, 2021	Activity RecognitionClustering	—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