Human Activity Recognition
136 papers with code • 4 benchmarks • 10 datasets
Classify various human activities
Benchmarks
These leaderboards are used to track progress in Human Activity Recognition
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Libraries
Use these libraries to find Human Activity Recognition models and implementationsDatasets
HAR
PAMAP2
WEAR
MPHOI-72
FLAG3D
HASCD
MPII Human Pose Descriptions
MOSAD
MuscleMap136
Most implemented papers
Deep Residual Bidir-LSTM for Human Activity Recognition Using Wearable Sensors
guillaume-chevalier/HAR-stacked-residual-bidir-LSTMs
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Human activity recognition (HAR) has become a popular topic in research because of its wide application.
Understanding the Vulnerability of Skeleton-based Human Activity Recognition via Black-box Attack
realcrane/BASAR-Black-box-Attack-on-Skeletal-Action-Recognition
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Via BASAR, we find on-manifold adversarial samples are extremely deceitful and rather common in skeletal motions, in contrast to the common belief that adversarial samples only exist off-manifold.
Kernel Cross-Correlator
Cross-correlator plays a significant role in many visual perception tasks, such as object detection and tracking.
A Probabilistic Logic Programming Event Calculus
MarcRoigVilamala/DeepProbCEP
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The input of our system is a set of time-stamped short-term activities (STA) detected on video frames.
Understanding and Improving Deep Neural Network for Activity Recognition
manish-vi/Human-Activity-Recognition
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After that, we extracted the significant features related to the activities and sent the features to the DNN-based fusion model, which improved the classification rate to 96. 1%.
Human activity recognition from skeleton poses
Human Action Recognition is an important task of Human Robot Interaction as cooperation between robots and humans requires that artificial agents recognise complex cues from the environment.
Human Activity Recognition from Wearable Sensor Data Using Self-Attention
saif-mahmud/self-attention-HAR
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In this regard, the existing recurrent or convolutional or their hybrid models for activity recognition struggle to capture spatio-temporal context from the feature space of sensor reading sequence.
Sequential Weakly Labeled Multi-Activity Localization and Recognition on Wearable Sensors using Recurrent Attention Networks
Recently, several attention mechanisms are proposed to handle the weakly labeled human activity data, which do not require accurate data annotation.
DANA: Dimension-Adaptive Neural Architecture for Multivariate Sensor Data
mmalekzadeh/dana
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We introduce a dimension-adaptive pooling (DAP) layer that makes DNNs flexible and more robust to changes in sensor availability and in sampling rate.
A benchmark of data stream classification for human activity recognition on connected objects
We measure both classification performance and resource consumption (runtime, memory, and power) of five usual stream classification algorithms, implemented in a consistent library, and applied to two real human activity datasets and to three synthetic datasets.
