Awesome Human Activity Recognition (mainly related/interacted to SENSOR data)

An up-to-date & curated list of Awesome IMU-based Human Activity Recognition(Ubiquitous Computing) papers, methods & resources. Please note that most of the collections of researches are mainly based on IMU data.

Acknowledgment

Many thanks to the useful publications and repos: Jingdong Wang, Awesome-Deep-Vision, Awesome-Deep-Learning-Papers, Awesome-Self-Supervised-Learning, Awesome-Semi-Supervised-Learning and Awesome-Crowd-Counting.

Contributing

Please feel free to contribute this list.

Conferences, Journals and Workshops

IJCAI, ACM MultiMedia, AAAI, KDD, ICDM, TKDE, TIP, TNNLS, TPAMI, TMM, Pattern Recognition, AI, Nature Communication, Nature Digital Medicine, ICPR, Sensors, Ubicomp(IMWUT Journal)
https://github.com/OxWearables/Oxford_Wearables_Activity_Recognition

Datasets

Capture-24 [link]
mHealth [link]
HHAR [link]
Opportunity [link]
PAMAP2 [link]
GOTOV [link]
REALDISP [link]
UCIDSADS [link]
MMAct [link]
TotalCapture [link]
WISDM [link]
MotionSense [link]
MobiAct [link]
Fenland [link]
Salad 50 [link]
DIP [link]
LARa [link]
Human Inertial Pose [link]
Kinetics-400 dataset [link]
UCF-101 dataset [link]

Tools

SimTK [link]
OpenSense [link]

Other related tasks

EEG analysis/prediction/modelling: https://github.com/meagmohit/EEG-Datasets

Potential Research Direction

Large-Scale/Diverse Dataset Research
Multi-Modality: sensor-vision, sensor-skeleton, sensor-3DPose, Sensor-Motion
window selection
Generative Model: e.g., cross modality data generation, IMU2Skeleton
Handling the NULL-Class problem
Open-World, Real-World: complex/non-repetitive activities
Advanced model
Data-cental: active learning, unsupervised learning, semi-supervised learning, self-supervised learning
Actiion Segmentation
Are the existing settings/models reliable?
Graph Representation
Motion-Capture, Kinetic
Privacy related
Interpretability
Data Imbalance
Domain Adaptation
Fine-Grained
Multi-Label
Federated Learning
Ensemble
Knowledge Integragation/distillation

Papers

Surveys & Overview

Body-Area Capacitive or Electric Field Sensing for Human Activity Recognition and Human-Computer Interaction: A Comprehensive Survey
<a name="DLHAR"></a> A Survey on Deep Learning for Human Activity Recognition (ACM Computing Surveys (CSUR)) [paper]
<a name="ML4SENSORHAR"></a> Applying Machine Learning for Sensor Data Analysis in Interactive Systems: Common Pitfalls of Pragmatic Use and Ways to Avoid Them (ACM Computing Surveys (CSUR)) [paper]
<a name="DL4SAR"></a> [DL4SAR] Deep Learning for Sensor-based Activity Recognition: A Survey (Pattern Recognition Letters) [paper][code]
<a name="Overview"></a> Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges, and Opportunities (ACM Computing Surveys (CSUR)) [paper]
<a name="Md"></a> Human Action Recognition from Various Data Modalities: A Review (IEEE TPAMI 2022) [paper] top AI Journal

2024

EarSleep: In-ear Acoustic-based Physical and Physiological Activity Recognition for Sleep Stage Detection
AutoAugHAR: Automated Data Augmentation for Sensor-based Human Activity Recognition
CrossHAR: Generalizing Cross-dataset Human Activity Recognition via Hierarchical Self-Supervised Pretraining
Changing Your Tune: Lessons for Using Music to Encourage Physical Activity
The EarSAVAS Dataset: Enabling Subject-Aware Vocal Activity Sensing on Earables
Self-supervised learning for Human Activity Recognition Using 700,000 Person-days of Wearable Data
IMUGPT 2.0: Language-Based Cross Modality Transfer for Sensor-Based Human Activity Recognition
HARMamba: Efficient Wearable Sensor Human Activity Recognition Based on Bidirectional Selective SSM
HyperHAR: Inter-sensing Device Bilateral Correlations and Hyper-correlations Learning Approach for Wearable Sensing Device Based Human Activity Recognition
Lateralization Effects in Electrodermal Activity Data Collected Using Wearable Devices
Body-Area Capacitive or Electric Field Sensing for Human Activity Recognition and Human-Computer Interaction: A Comprehensive Survey
exHAR: An Interface for Helping Non-Experts Develop and Debug Knowledge-based Human Activity Recognition Systems
Kirigami: Lightweight Speech Filtering for Privacy-Preserving Activity Recognition using Audio
Co-Designing Sensory Feedback for Wearables to Support Physical Activity through Body Sensations
Semantic Loss: A New Neuro-Symbolic Approach for Context-Aware Human Activity Recognition
CAvatar: Real-time Human Activity Mesh Reconstruction via Tactile Carpets
Deep Heterogeneous Contrastive Hyper-Graph Learning for In-the-Wild Context-Aware Human Activity Recognition
SF-Adapter: Computational-Efficient Source-Free Domain Adaptation for Human Activity Recognition
Spatial-Temporal Masked Autoencoder for Multi-Device Wearable Human Activity Recognition
Optimization-Free Test-Time Adaptation for Cross-Person Activity Recognition
TextureSight: Texture Detection for Routine Activity Awareness with Wearable Laser Speckle Imaging
TS2ACT: Few-Shot Human Activity Sensing with Cross-Modal Co-Learning

2023

Integrating Gaze and Mouse Via Joint Cross-Attention Fusion Net for Students' Activity Recognition in E-learning
Integrating Gaze and Mouse Via Joint Cross-Attention Fusion Net for Students' Activity Recognition in E-learning
VAX: Using Existing Video and Audio-based Activity Recognition Models to Bootstrap Privacy-Sensitive Sensors
LAUREATE: A Dataset for Supporting Research in Affective Computing and Human Memory Augmentation
MMTSA: Multi-Modal Temporal Segment Attention Network for Efficient Human Activity Recognition
HMGAN: A Hierarchical Multi-Modal Generative Adversarial Network Model for Wearable Human Activity Recognition
TAO: Context Detection from Daily Activity Patterns Using Temporal Analysis and Ontology
HAKE: Human Activity Knowledge Engine [link]
PhysiQ: Off-site Quality Assessment of Exercise in Physical Therapy [link]
SAMoSA: Sensing Activities with Motion and Subsampled Audio [link]
Physical-aware Cross-modal Adversarial Network for Wearable Sensor-based Human Action Recognition [link]
IMU2CLIP: Multimodal Contrastive Learning for IMU Motion Sensors from Egocentric Videos and Text
Real-time Context-Aware Multimodal Network for Activity and Activity-Stage Recognition from Team Communication in Dynamic Clinical Settings
X-CHAR: A Concept-based Explainable Complex Human Activity Recognition Model
Hierarchical Clustering-based Personalized Federated Learning for Robust and Fair Human Activity Recognition
AMIR: Active Multimodal Interaction Recognition from Video and Network Traffic in Connected Environments
Narrative-Based Visual Feedback to Encourage Sustained Physical Activity: A Field Trial of the WhoIsZuki Mobile Health Platform
Human Parsing with Joint Learning for Dynamic mmWave Radar Point Cloud
RF-CM: Cross-Modal Framework for RF-enabled Few-Shot Human Activity Recognition
PrISM-Tracker: A Framework for Multimodal Procedure Tracking Using Wearable Sensors and State Transition Information with User-Driven Handling of Errors and Uncertainty
Self-supervised Learning for Human Activity Recognition Using 700,000 Person-days of Wearable Data
GLOBEM: Cross-Dataset Generalization of Longitudinal Human Behavior Modeling
TransFloor: Transparent Floor Localization for Crowdsourcing Instant Delivery
Understanding the Mechanism of Through-Wall Wireless Sensing: A Model-based Perspective
Unveiling Causal Attention in Dogs' Eyes with Smart Eyewear
MHCCL: Masked Hierarchical Cluster-wise Contrastive Learning for Multivariate Time Series

2022

Self-Supervised Contrastive Pre-Training for Time Series via Time-Frequency Consistency
MaeFE: Masked Autoencoders Family of Electrocardiogram for Self-supervised Pre-training and Transfer Learning
A Simple Self-Supervised IMU Denoising Method For Inertial Aided Navigation
Adaptive Memory Networks with Self-supervised Learning for Unsupervised Anomaly Detection
MHCCL: Masked Hierarchical Cluster-wise Contrastive Learning for Multivariate Time Series
FLAME: Federated Learning across Multi-device Environments
Longitudinal cardio-respiratory fitness prediction through wearables in free-living environments
Self-supervised transfer learning of physiological representations from free-living wearable data
Learning Generalizable Physiological Representations from Large-scale Wearable Data
Application-Driven AI Paradigm for Human Action Recognition
A hybrid accuracy-and energy-aware human activity recognition model in IoT environment
Predicting Performance Improvement of Human Activity Recognition Model by Additional Data Collection
SAMoSA: Sensing Activities with Motion and Subsampled Audio
Towards Ubiquitous Personalized Music Recommendation with Smart Bracelets
Towards a Dynamic Inter-Sensor Correlations Learning Framework for Multi-Sensor-Based Wearable Human Activity Recognition
Augmented Adversarial Learning for Human Activity Recognition with Partial Sensor Sets
Bootstrapping Human Activity Recognition Systems for Smart Homes from Scratch
Towards a Dynamic Inter-Sensor Correlations Learning Framework for Multi-Sensor-Based Wearable Human Activity Recognition [link]
Cosmo: Contrastive Fusion Learning with Small Data for Multimodal Human Activity Recognition
What Makes Good Contrastive Learning on Small-Scale Wearable-based Tasks?
ClusterFL: a similarity-aware federated learning system for human activity recognition
Human Action Recognition from Various Data Modalities: A Review (IEEE TPAMI 2022 (top AI Journal))
Semantic-Discriminative Mixup for Generalizable Sensor-based Cross-domain Activity Recognition
Are You Left Out?: An Efficient and Fair Federated Learning for Personalized Profiles on Wearable Devices of Inferior Networking Conditions
Progressive Cross-modal Knowledge Distillation for Human Action Recognition [link]
Leveraging Sound and Wrist Motion to Detect Activities of Daily Living with Commodity Smartwatches
I Want to Know Your Hand: Authentication on Commodity Mobile Phones Based on Your Hand's Vibrations
CSI:DeSpy: Enabling Effortless Spy Camera Detection via Passive Sensing of User Activities and Bitrate Variations
Acceleration-based Activity Recognition of Repetitive Works with Lightweight Ordered-work Segmentation Network
IF-ConvTransformer: A Framework for Human Activity Recognition Using IMU Fusion and ConvTransformer
Quali-Mat: Evaluating the Quality of Execution in Body-Weight Exercises with a Pressure Sensitive Sports Mat
Non-Bayesian Out-of-Distribution Detection Applied to CNN Architectures for Human Activity Recognition
Resource-Efficient Continual Learning for Sensor-Based Human Activity Recognition
Beyond the Gates of Euclidean Space: Temporal-Discrimination-Fusions and Attention-based Graph Neural Network for Human Activity Recognition
LiteHAR: LIGHTWEIGHT HUMAN ACTIVITY RECOGNITION FROM WIFI SIGNALS WITH RANDOM CONVOLUTION KERNELS
A Review on Topological Data Analysis in Human Activity Recognition
Deep CNN-LSTM with Self-Attention Model for Human Activity Recognition using Wearable Sensor
Zero-Shot Learning for IMU-Based Activity Recognition Using Video Embeddings
Deep Transfer Learning with Graph Neural Network for Sensor-Based Human Activity Recognition
Meta-learning meets the Internet of Things: Graph prototypical models for sensor-based human activity recognition
Federated Multi-Task Learning
Unsupervised Human Activity Recognition Using the Clustering Approach: A Review
Hierarchical Self Attention Based Autoencoder for Open-Set Human Activity Recognition
Assessing the State of Self-Supervised Human Activity Recognition using Wearables
ROBUST AND EFFICIENT UNCERTAINTY AWARE BIOSIGNAL CLASSIFICATION VIA EARLY EXIT ENSEMBLES
Machine learning detects altered spatial navigation features in outdoor behaviour of Alzheimer’s disease patients
Evaluating Contrastive Learning on Wearable Timeseries for Downstream Clinical Outcomes
Segmentation-free Heart Pathology Detection Using Deep Learning
Anticipatory Detection of Compulsive Body-focused Repetitive Behaviors with Wearables
Assessing the State of Self-Supervised Human Activity Recognition using Wearables
Method and system for automatic extraction of virtual on-body inertial measurement units
Enhancing the Security & Privacy of Wearable Brain-Computer Interfaces
Detecting Smartwatch-Based Behavior Change in Response to a Multi-Domain Brain Health Intervention
ColloSSL: Collaborative Self-Supervised Learning for Human Activity Recognition
Multi-scale Deep Feature Learning for Human Activity Recognition Using Wearable Sensors
Improving Wearable-Based Activity Recognition Using Image Representations
Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges
A recurrent neural network architecture to model physical activity energy expenditure in older people
Application of artificial intelligence in wearable devices: Opportunities and challenges
A Close Look into Human Activity Recognition Models using Deep Learning