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 261–270 of 1322 papers

Title	Date	Tasks	Status	Score
DYSAN: Dynamically sanitizing motion sensor data against sensitive inferences through adversarial networks	Mar 23, 2020	Activity RecognitionAttribute	CodeCode Available	5
Approaches to human activity recognition via passive radar	Oct 31, 2024	Activity RecognitionHuman Activity Recognition	CodeCode Available	5
DiTMoS: Delving into Diverse Tiny-Model Selection on Microcontrollers	Mar 14, 2024	Activity RecognitionDiversity	CodeCode Available	5
Does SpatioTemporal information benefit Two video summarization benchmarks?	Oct 4, 2024	Activity RecognitionVideo Summarization	CodeCode Available	5
Discriminatively Learned Hierarchical Rank Pooling Networks	May 30, 2017	Activity RecognitionBilevel Optimization	CodeCode Available	5
Discriminating Spatial and Temporal Relevance in Deep Taylor Decompositions for Explainable Activity Recognition	Aug 5, 2019	Action RecognitionActivity Recognition	CodeCode Available	5
Distributed Online Learning of Event Definitions	May 5, 2017	Activity RecognitionForm	CodeCode Available	5
Domain Adaptation Under Behavioral and Temporal Shifts for Natural Time Series Mobile Activity Recognition	Jul 10, 2022	Activity RecognitionContrastive Learning	CodeCode Available	5
Defending Black-box Skeleton-based Human Activity Classifiers	Mar 9, 2022	Activity RecognitionHuman Activity Recognition	CodeCode Available	5
Differentially Private Integrated Decision Gradients (IDG-DP) for Radar-based Human Activity Recognition	Nov 4, 2024	Activity RecognitionHuman Activity Recognition	CodeCode Available	5

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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