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 1151–1200 of 1322 papers

TitleStatusHype
Activity and Subject Detection for UCI HAR Dataset with & without missing Sensor DataCode0
Resolution-Adaptive Micro-Doppler Spectrogram for Human Activity RecognitionCode0
Weak-Annotation of HAR Datasets using Vision Foundation ModelsCode0
Hang-Time HAR: A Benchmark Dataset for Basketball Activity Recognition using Wrist-Worn Inertial SensorsCode0
Subject Cross Validation in Human Activity RecognitionCode0
FedAli: Personalized Federated Learning with Aligned Prototypes through Optimal TransportCode0
Super Low Resolution RF Powered Accelerometers for Alerting on Hospitalized Patient Bed ExitsCode0
Hard Regularization to Prevent Deep Online Clustering Collapse without Data AugmentationCode0
Feature engineering workflow for activity recognition from synchronized inertial measurement unitsCode0
Exploring Video-Based Driver Activity Recognition under Noisy LabelsCode0
Defending Black-box Skeleton-based Human Activity ClassifiersCode0
HARMamba: Efficient and Lightweight Wearable Sensor Human Activity Recognition Based on Bidirectional MambaCode0
Chirality Nets for Human Pose RegressionCode0
Cadence: A Practical Time-series Partitioning Algorithm for Unlabeled IoT Sensor StreamsCode0
ATARS: An Aerial Traffic Atomic Activity Recognition and Temporal Segmentation DatasetCode0
MEx: Multi-modal Exercises Dataset for Human Activity RecognitionCode0
RHM: Robot House Multi-view Human Activity Recognition DatasetCode0
MIFI: MultI-camera Feature Integration for Roust 3D Distracted Driver Activity RecognitionCode0
Explaining Human Activity Recognition with SHAP: Validating Insights with Perturbation and Quantitative MeasuresCode0
Hierarchical Attentive Recurrent TrackingCode0
Hierarchical Deep Temporal Models for Group Activity RecognitionCode0
Hierarchical Relational Networks for Group Activity Recognition and RetrievalCode0
Evaluating Spiking Neural Network On Neuromorphic Platform For Human Activity RecognitionCode0
Hierarchical Temporal Convolution Network:Towards Privacy-Centric Activity RecognitionCode0
Deep Residual Bidir-LSTM for Human Activity Recognition Using Wearable SensorsCode0
Towards Fairness in Visual Recognition: Effective Strategies for Bias MitigationCode0
Mindful Active LearningCode0
Unsupervised Deep Learning-based clustering for Human Activity RecognitionCode0
Robotic Vision and Multi-View Synergy: Action and activity recognition in assisted living scenariosCode0
Towards Hardware-Aware Tractable Learning of Probabilistic ModelsCode0
Human Activity Recognition: A Spatio-temporal Image Encoding of 3D Skeleton Data for Online Action DetectionCode0
MMTSA: Multimodal Temporal Segment Attention Network for Efficient Human Activity RecognitionCode0
Personalized Activity Recognition with Deep Triplet EmbeddingsCode0
Human Activity Recognition Based on Wearable Sensor Data: A Standardization of the State-of-the-ArtCode0
Deep Learning for Sensor-based Activity Recognition: A SurveyCode0
Adversarial Domain Adaptation for Cross-user Activity Recognition Using Diffusion-based Noise-centred LearningCode0
MobiRNN: Efficient Recurrent Neural Network Execution on Mobile GPUCode0
Human activity recognition from skeleton posesCode0
Ensemble diverse hypotheses and knowledge distillation for unsupervised cross-subject adaptationCode0
Accoustate: Auto-annotation of IMU-generated Activity Signatures under Smart InfrastructureCode0
Human Activity Recognition in an Open WorldCode0
Zero-Shot Activity Recognition with Verb Attribute InductionCode0
Adversarial Attacks on Deep Neural Networks for Time Series ClassificationCode0
Towards Multi-User Activity Recognition through Facilitated Training Data and Deep Learning for Human-Robot Collaboration ApplicationsCode0
Situation Recognition: Visual Semantic Role Labeling for Image UnderstandingCode0
Deep Heterogeneous Contrastive Hyper-Graph Learning for In-the-Wild Context-Aware Human Activity RecognitionCode0
Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical BayesCode0
RWF-2000: An Open Large Scale Video Database for Violence DetectionCode0
Skeleton-Based Action Recognition with Spatial-Structural Graph ConvolutionCode0
SALIENCE: An Unsupervised User Adaptation Model for Multiple Wearable Sensors Based Human Activity RecognitionCode0
Show:102550
← PrevPage 24 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