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 201–225 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
Initial Findings on Sensor based Open Vocabulary Activity Recognition via Text Embedding Inversion—0
IoT-Based Real-Time Medical-Related Human Activity Recognition Using Skeletons and Multi-Stage Deep Learning for HealthcareCode0
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
Show:102550
← PrevPage 9 of 53Next →
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