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 591–600 of 1322 papers

Title	Date	Tasks	Status
Contrastive Learning for Time Series on Dynamic Graphs	Sep 21, 2022	Activity RecognitionAnomaly Detection	—Unverified
A Prospective Approach for Human-to-Human Interaction Recognition from Wi-Fi Channel Data using Attention Bidirectional Gated Recurrent Neural Network with GUI Application Implementation	Feb 16, 2022	Activity RecognitionHuman Activity Recognition	—Unverified
Frequency-Aware Masked Autoencoders for Human Activity Recognition using Accelerometers	Feb 17, 2025	Activity RecognitionHuman Activity Recognition	—Unverified
Group Activity Recognition via Dynamic Composition and Interaction	May 9, 2023	Activity RecognitionGroup Activity Recognition	—Unverified
Compact CNN for Indexing Egocentric Videos	Apr 28, 2015	Activity RecognitionOptical Flow Estimation	—Unverified
Guided-GAN: Adversarial Representation Learning for Activity Recognition with Wearables	Oct 12, 2021	Activity RecognitionGenerative Adversarial Network	—Unverified
Contrastive Predictive Coding for Human Activity Recognition	Dec 9, 2020	Activity RecognitionHuman Activity Recognition	—Unverified
Hadamard Domain Training with Integers for Class Incremental Quantized Learning	Oct 5, 2023	Activity Recognitionclass-incremental learning	—Unverified
HAMLET: A Hierarchical Multimodal Attention-based Human Activity Recognition Algorithm	Aug 3, 2020	Activity RecognitionHuman Activity Recognition	—Unverified
Appearance Based Robot and Human Activity Recognition System	Feb 4, 2016	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