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 791–800 of 1322 papers

Title	Date	Tasks	Status
Guided-GAN: Adversarial Representation Learning for Activity Recognition with Wearables	Oct 12, 2021	Activity RecognitionGenerative Adversarial Network	—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
Handling Variable-Dimensional Time Series with Graph Neural Networks	Jul 1, 2020	Activity RecognitionGraph Neural Network	—Unverified
HAPRec: Hybrid Activity and Plan Recognizer	Apr 28, 2020	Action RecognitionActivity Recognition	—Unverified
HAR-DoReMi: Optimizing Data Mixture for Self-Supervised Human Activity Recognition Across Heterogeneous IMU Datasets	Mar 16, 2025	Activity RecognitionHuman Activity Recognition	—Unverified
HARGPT: Are LLMs Zero-Shot Human Activity Recognizers?	Mar 5, 2024	Activity RecognitionHuman Activity Recognition	—Unverified
HAR-Net:Fusing Deep Representation and Hand-crafted Features for Human Activity Recognition	Oct 25, 2018	Activity RecognitionDeep Learning	—Unverified
HENASY: Learning to Assemble Scene-Entities for Egocentric Video-Language Model	Jun 1, 2024	Action RecognitionActivity Recognition	—Unverified
Heterogeneous Hidden Markov Models for Sleep Activity Recognition from Multi-Source Passively Sensed Data	Nov 8, 2022	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