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Human Activity Recognition

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하위 태스크: 1
평가표: 8
보존된 평가 기록: 16

Classify various human activities

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://bitbucket.org/edge-team-leat/microai_public

공식 코드

Quantization and Deployment of Deep Neural Networks on Microcontrollers

https://github.com/AnitaEpsilon/HAR

공식 코드

Human Activity Recognition using Continuous Wavelet Transform and Convolutional Neural Networks

https://github.com/B-HAR-HumanActivityRecognition/B-HAR

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B-HAR: an open-source baseline framework for in depth study of human activity recognition datasets and workflows

https://github.com/Breezelled/COMODO

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COMODO: Cross-Modal Video-to-IMU Distillation for Efficient Egocentric Human Activity Recognition

https://github.com/CDAC-lab/ETFA-Workshop/blob/main/CNN%20and%20LSTM%20for%20Human%20Activity%20Recognition.ipynb

공식 코드

Human Activity Recognition using Multi-Head CNN followed by LSTM

https://github.com/Chain123/Meta-HAR

공식 코드

Meta-HAR: Federated Representation Learning for Human Activity Recognition

https://github.com/Chiaraplizz/ST-TR

공식 코드

Skeleton-based Action Recognition via Spatial and Temporal Transformer Networks

https://github.com/Claydon-Wang/OFTTA

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Optimization-Free Test-Time Adaptation for Cross-Person Activity Recognition

https://github.com/Computational-Imaging-Lab-IITM/HAR-DVS

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Dynamic Vision Sensors for Human Activity Recognition

https://github.com/DavideBuffelli/TrASenD

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Attention-Based Deep Learning Framework for Human Activity Recognition with User Adaptation

https://github.com/Forsad/Stable-Polynomial-Train

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A Training Framework for Optimal and Stable Training of Polynomial Neural Networks

https://github.com/GMouYes/DHC_HGL

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Deep Heterogeneous Contrastive Hyper-Graph Learning for In-the-Wild Context-Aware Human Activity Recognition

https://github.com/Gbouna/MAK-GCN

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Multi-Head Adaptive Graph Convolution Network for Sparse Point Cloud-Based Human Activity Recognition

https://github.com/GeetDsa/Activity_Recognition_3D_CNN

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An IoT Based Framework For Activity Recognition Using Deep Learning Technique

https://github.com/I2RDL2/ASTAR-HAR

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A*HAR: A New Benchmark towards Semi-supervised learning for Class-imbalanced Human Activity Recognition

https://github.com/IoBT-VISTEC/SleepPoseNet

공식 코드

SleepPoseNet: Multi-View Learning for Sleep Postural Transition Recognition Using UWB

https://github.com/KennCoder7/RAN

공식 코드

Sequential Weakly Labeled Multi-Activity Localization and Recognition on Wearable Sensors using Recurrent Attention Networks

https://github.com/Lou1sM/HAR

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Efficient Deep Clustering of Human Activities and How to Improve Evaluation

https://github.com/Mvrjustid/IMWUT-Hierarchical-HAR-PBD

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Leveraging Activity Recognition to Enable Protective Behavior Detection in Continuous Data

https://github.com/Oshana/ESWA

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A Comparison of Deep Learning and Established Methods for Calf Behaviour Monitoring

https://github.com/OxWearables/ssl-wearables

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Self-supervised Learning for Human Activity Recognition Using 700,000 Person-days of Wearable Data

https://github.com/RBurchard/hd-epic-tap

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Enhancing Wearable Tap Water Audio Detection through Subclass Annotation in the HD-Epic Dataset

https://github.com/RanaMostafaAbdElMohsen/Human_Activity_Recognition_using_Wearable_Sensors_Review_Challenges_Evaluation_Benchmark

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Human Activity Recognition using Wearable Sensors: Review, Challenges, Evaluation Benchmark

https://github.com/Rxannro/SWL-Adapt

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SWL-Adapt: An Unsupervised Domain Adaptation Model with Sample Weight Learning for Cross-User Wearable Human Activity Recognition

https://github.com/SPEECHCOG/data2vec_maiju

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Evaluation of self-supervised pre-training for automatic infant movement classification using wearable movement sensors

https://github.com/StrohmayerJ/wallhack1.8k

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Data Augmentation Techniques for Cross-Domain WiFi CSI-based Human Activity Recognition

https://github.com/Xu-Linfeng/UESTC_MMEA_CL_main

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Towards Continual Egocentric Activity Recognition: A Multi-modal Egocentric Activity Dataset for Continual Learning

https://github.com/ZikangLeng/IMUGPT

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Generating Virtual On-body Accelerometer Data from Virtual Textual Descriptions for Human Activity Recognition

https://github.com/abduallahmohamed/har-gcnn

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HAR-GCNN: Deep Graph CNNs for Human Activity Recognition From Highly Unlabeled Mobile Sensor Data

https://github.com/ahoelzemann/annotationmatters

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A Matter of Annotation: An Empirical Study on In Situ and Self-Recall Activity Annotations from Wearable Sensors

https://github.com/ahoelzemann/hangtime_har

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Hang-Time HAR: A Benchmark Dataset for Basketball Activity Recognition using Wrist-Worn Inertial Sensors

https://github.com/allanmsouza/acsp-fl

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Adaptive Client Selection with Personalization for Communication Efficient Federated Learning

https://github.com/anakin2555/decomposewhar

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Decomposing and Fusing Intra- and Inter-Sensor Spatio-Temporal Signal for Multi-Sensor Wearable Human Activity Recognition

https://github.com/anirudhsom/PI-Net

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PI-Net: A Deep Learning Approach to Extract Topological Persistence Images

https://github.com/anjanaw/MEx

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MEx: Multi-modal Exercises Dataset for Human Activity Recognition

https://github.com/arturjordao/WearableSensorData

공식 코드

Human Activity Recognition Based on Wearable Sensor Data: A Standardization of the State-of-the-Art

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