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

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Showing 151–200 of 1322 papers

TitleStatusHype
Human Activity Recognition with Convolutional Neural NetowrksCode0
Hybrid CNN-Dilated Self-attention Model Using Inertial and Body-Area Electrostatic Sensing for Gym Workout Recognition, Counting, and User AuthentificationCode0
Incremental Learning of Event Definitions with Inductive Logic ProgrammingCode0
Human Activity Recognition in an Open WorldCode0
Human Activity Recognition Based on Wearable Sensor Data: A Standardization of the State-of-the-ArtCode0
Human Activity Recognition: A Spatio-temporal Image Encoding of 3D Skeleton Data for Online Action DetectionCode0
Human activity recognition from skeleton posesCode0
Human Activity Recognition using Continuous Wavelet Transform and Convolutional Neural NetworksCode0
Hierarchical Relational Networks for Group Activity Recognition and RetrievalCode0
HARMamba: Efficient and Lightweight Wearable Sensor Human Activity Recognition Based on Bidirectional MambaCode0
A Matter of Annotation: An Empirical Study on In Situ and Self-Recall Activity Annotations from Wearable SensorsCode0
A Comparison of Deep Learning and Established Methods for Calf Behaviour MonitoringCode0
AutoGCN -- Towards Generic Human Activity Recognition with Neural Architecture SearchCode0
Hard Regularization to Prevent Deep Online Clustering Collapse without Data AugmentationCode0
Hierarchical Temporal Convolution Network:Towards Privacy-Centric Activity RecognitionCode0
Human Activity Recognition using Multi-Head CNN followed by LSTMCode0
LSTA: Long Short-Term Attention for Egocentric Action RecognitionCode0
Group Activity Recognition Using Joint Learning of Individual Action Recognition and People GroupingCode0
Alignment-based conformance checking over probabilistic eventsCode0
SPARTAN: Self-supervised Spatiotemporal Transformers Approach to Group Activity RecognitionCode0
Generative Pretrained Embedding and Hierarchical Irregular Time Series Representation for Daily Living Activity RecognitionCode0
Generalizable Low-Resource Activity Recognition with Diverse and Discriminative Representation LearningCode0
Generalized Relevance Learning Grassmann QuantizationCode0
GeoERM: Geometry-Aware Multi-Task Representation Learning on Riemannian ManifoldsCode0
Fine-grained Activity Recognition in Baseball VideosCode0
FedHome: Cloud-Edge based Personalized Federated Learning for In-Home Health MonitoringCode0
A Hierarchical Deep Temporal Model for Group Activity RecognitionCode0
FAR: Fourier Aerial Video RecognitionCode0
Exploring Video-Based Driver Activity Recognition under Noisy LabelsCode0
Feature engineering workflow for activity recognition from synchronized inertial measurement unitsCode0
Explaining Human Activity Recognition with SHAP: Validating Insights with Perturbation and Quantitative MeasuresCode0
A*HAR: A New Benchmark towards Semi-supervised learning for Class-imbalanced Human Activity RecognitionCode0
FedAli: Personalized Federated Learning with Aligned Prototypes through Optimal TransportCode0
Attention is All We Need: Nailing Down Object-centric Attention for Egocentric Activity RecognitionCode0
Out-of-Distribution Representation Learning for Time Series ClassificationCode0
Fully Convolutional Network Bootstrapped by Word Encoding and Embedding for Activity Recognition in Smart HomesCode0
Guidelines for Augmentation Selection in Contrastive Learning for Time Series ClassificationCode0
Audio-Based Activities of Daily Living (ADL) Recognition with Large-Scale Acoustic Embeddings from Online VideosCode0
ATARS: An Aerial Traffic Atomic Activity Recognition and Temporal Segmentation DatasetCode0
Glimpse Clouds: Human Activity Recognition from Unstructured Feature PointsCode0
Enhancing Wearable Tap Water Audio Detection through Subclass Annotation in the HD-Epic DatasetCode0
Ensemble diverse hypotheses and knowledge distillation for unsupervised cross-subject adaptationCode0
Attention-Refined Unrolling for Sparse Sequential micro-Doppler ReconstructionCode0
Activity-Biometrics: Person Identification from Daily ActivitiesCode0
Enhanced Spatio- Temporal Image Encoding for Online Human Activity RecognitionCode0
Easy Ensemble: Simple Deep Ensemble Learning for Sensor-Based Human Activity RecognitionCode0
Hierarchical Attentive Recurrent TrackingCode0
Hierarchical Deep Temporal Models for Group Activity RecognitionCode0
Robust Explainer Recommendation for Time Series ClassificationCode0
Dynamic Vision Sensors for Human Activity RecognitionCode0
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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