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 1221–1230 of 1322 papers

Title	Date	Tasks	Status
Continual Learning in Human Activity Recognition: an Empirical Analysis of Regularization	Jul 6, 2020	Activity RecognitionContinual Learning	—Unverified
Continual Learning in Sensor-based Human Activity Recognition: an Empirical Benchmark Analysis	Apr 19, 2021	Activity RecognitionContinual Learning	—Unverified
Continuous Human Activity Recognition using a MIMO Radar for Transitional Motion Analysis	Apr 12, 2023	Activity RecognitionHuman Activity Recognition	—Unverified
Contrastive Learning for Time Series on Dynamic Graphs	Sep 21, 2022	Activity RecognitionAnomaly Detection	—Unverified
Contrastive Left-Right Wearable Sensors (IMUs) Consistency Matching for HAR	Nov 21, 2023	Activity RecognitionHuman Activity Recognition	—Unverified
Contrastive Predictive Coding for Human Activity Recognition	Dec 9, 2020	Activity RecognitionHuman Activity Recognition	—Unverified
ConViViT -- A Deep Neural Network Combining Convolutions and Factorized Self-Attention for Human Activity Recognition	Oct 22, 2023	Activity RecognitionHuman Activity Recognition	—Unverified
Convolutional Relational Machine for Group Activity Recognition	Apr 5, 2019	Activity RecognitionGroup Activity Recognition	—Unverified
CoSS: Co-optimizing Sensor and Sampling Rate for Data-Efficient AI in Human Activity Recognition	Jan 3, 2024	Activity RecognitionHuman Activity Recognition	—Unverified
Creating a Large-scale Synthetic Dataset for Human Activity Recognition	Jul 21, 2020	Activity RecognitionHuman Activity Recognition	—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