SOTAVerified

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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 201–250 of 1322 papers

TitleStatusHype
Human Activity Recognition with a 6.5 GHz Reconfigurable Intelligent Surface for Wi-Fi 6E—0
Decomposing and Fusing Intra- and Inter-Sensor Spatio-Temporal Signal for Multi-Sensor Wearable Human Activity RecognitionCode0
Benchmarking Classical, Deep, and Generative Models for Human Activity Recognition—0
IoT-Based Real-Time Medical-Related Human Activity Recognition Using Skeletons and Multi-Stage Deep Learning for HealthcareCode0
Initial Findings on Sensor based Open Vocabulary Activity Recognition via Text Embedding Inversion—0
Collaborative Human Activity Recognition with Passive Inter-Body Electrostatic Field—0
Enforcing Fundamental Relations via Adversarial Attacks on Input Parameter Correlations—0
Multivariate Human Activity Segmentation: Systematic Benchmark with ClaSPCode0
OV-HHIR: Open Vocabulary Human Interaction Recognition Using Cross-modal Integration of Large Language Models—0
Transformer-Based Contrastive Meta-Learning For Low-Resource Generalizable Activity Recognition—0
Generative Pretrained Embedding and Hierarchical Irregular Time Series Representation for Daily Living Activity RecognitionCode0
Hierarchical Temporal Convolution Network:Towards Privacy-Centric Activity RecognitionCode0
Choose Your Explanation: A Comparison of SHAP and GradCAM in Human Activity RecognitionCode0
Generalizable Sensor-Based Activity Recognition via Categorical Concept Invariant Learning—0
Wearable Accelerometer Foundation Models for Health via Knowledge Distillation—0
Beyond Confusion: A Fine-grained Dialectical Examination of Human Activity Recognition Benchmark Datasets—0
Exploring the Impact of Synthetic Data on Human Gesture Recognition Tasks Using GANs—0
Action Recognition based Industrial Safety Violation Detection—0
Temporally Consistent Dynamic Scene Graphs: An End-to-End Approach for Action Tracklet Generation—0
AsyMov: Integrated Sensing and Communications with Asynchronous Moving Devices—0
Heterogeneous Relationships of Subjects and Shapelets for Semi-supervised Multivariate Series Classification—0
Evolving Markov Chains: Unsupervised Mode Discovery and Recognition from Data Streams—0
Adaptive Client Selection with Personalization for Communication Efficient Federated LearningCode0
Resolution-Adaptive Micro-Doppler Spectrogram for Human Activity RecognitionCode0
Bi-LSTM neural network for EEG-based error detection in musicians' performance—0
FedAli: Personalized Federated Learning with Aligned Prototypes through Optimal TransportCode0
Process-aware Human Activity Recognition—0
FedSub: Introducing class-aware Subnetworks Fusion to Enhance Personalized Federated Learning in Ubiquitous Systems—0
Past, Present, and Future of Sensor-Based Human Activity Recognition Using Wearables: A Surveying Tutorial on a Still Challenging Task—0
Federated Split Learning for Human Activity Recognition with Differential Privacy—0
WiFlexFormer: Efficient WiFi-Based Person-Centric SensingCode0
Explaining Human Activity Recognition with SHAP: Validating Insights with Perturbation and Quantitative MeasuresCode0
ARN-LSTM: A Multi-Stream Fusion Model for Skeleton-based Action Recognition—0
Differentially Private Integrated Decision Gradients (IDG-DP) for Radar-based Human Activity RecognitionCode0
Approaches to human activity recognition via passive radarCode0
First Place Solution to the ECCV 2024 ROAD++ Challenge @ ROAD++ Atomic Activity Recognition 2024—0
LiGAR: LiDAR-Guided Hierarchical Transformer for Multi-Modal Group Activity Recognition—0
Activity Recognition on Avatar-Anonymized Datasets with Masked Differential Privacy—0
CKSP: Cross-species Knowledge Sharing and Preserving for Universal Animal Activity Recognition—0
Mukhtasir-Khail-Net: An Ultra-Efficient Convolutional Neural Network for Sports Activity Recognition with Wearable Inertial SensorsCode0
Improving the Multi-label Atomic Activity Recognition by Robust Visual Feature and Advanced Attention @ ROAD++ Atomic Activity Recognition 2024—0
Vital Insight: Assisting Experts' Context-Driven Sensemaking of Multi-modal Personal Tracking Data Using Visualization and Human-In-The-Loop LLM Agents—0
Transformer-Based Approaches for Sensor-Based Human Activity Recognition: Opportunities and Challenges—0
Scaling Wearable Foundation Models—0
ARIC: An Activity Recognition Dataset in Classroom Surveillance Images—0
X-Fi: A Modality-Invariant Foundation Model for Multimodal Human Sensing—0
Large Model for Small Data: Foundation Model for Cross-Modal RF Human Activity Recognition—0
Real-time Monitoring of Lower Limb Movement Resistance Based on Deep Learning—0
FMCW Radar Principles and Human Activity Recognition Systems: Foundations, Techniques, and Applications—0
Generalizable Indoor Human Activity Recognition Method Based on Micro-Doppler Corner Point Cloud and Dynamic Graph Learning—0
Show:102550
← PrevPage 5 of 27Next →
All datasetsRWF-2000Stanford40First-Person Hand Action BenchmarkSelf-stimulatory Behavior Dataset

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Structured Keypoint PoolingAccuracy93.4—Unverified
2Semi-Supervised Hard Attention (SSHA); pretrained on Deepmind Kinetics datasetAccuracy90.4—Unverified
3Human Skeletons + Change DetectionAccuracy90.25—Unverified
4Separable Convolutional LSTMAccuracy89.75—Unverified
5SPIL ConvolutionAccuracy89.3—Unverified
6Flow Gated NetworkAccuracy87.25—Unverified
#ModelMetricClaimedVerifiedStatus
1FocusCLIPTop-3 Accuracy (%)10.47—Unverified
2CLIPTop-3 Accuracy (%)6.49—Unverified
#ModelMetricClaimedVerifiedStatus
1Boutaleb et al.1:1 Accuracy97.91—Unverified
#ModelMetricClaimedVerifiedStatus
1all-landmark-modelActivity Recognition0.76—Unverified