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 1–50 of 1322 papers

TitleStatusHype
ALS-HAR: Harnessing Wearable Ambient Light Sensors to Enhance IMU-based Human Activity RecogntionCode3
HARDVS: Revisiting Human Activity Recognition with Dynamic Vision SensorsCode3
Human Activity Recognition using RGB-Event based Sensors: A Multi-modal Heat Conduction Model and A Benchmark DatasetCode2
SensorLLM: Human-Intuitive Alignment of Multivariate Sensor Data with LLMs for Activity RecognitionCode2
NeuFlow: Real-time, High-accuracy Optical Flow Estimation on Robots Using Edge DevicesCode2
Class-incremental Learning for Time Series: Benchmark and EvaluationCode2
WiMANS: A Benchmark Dataset for WiFi-based Multi-user Activity SensingCode2
SenseFi: A Library and Benchmark on Deep-Learning-Empowered WiFi Human SensingCode2
Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency ConsistencyCode2
AutoFi: Towards Automatic WiFi Human Sensing via Geometric Self-Supervised LearningCode2
Deep learning for time series classificationCode2
RadMamba: Efficient Human Activity Recognition through Radar-based Micro-Doppler-Oriented Mamba State-Space ModelCode1
Multi-Head Adaptive Graph Convolution Network for Sparse Point Cloud-Based Human Activity RecognitionCode1
COMODO: Cross-Modal Video-to-IMU Distillation for Efficient Egocentric Human Activity RecognitionCode1
SGA-INTERACT: A 3D Skeleton-based Benchmark for Group Activity Understanding in Modern Basketball TacticCode1
RelCon: Relative Contrastive Learning for a Motion Foundation Model for Wearable DataCode1
DATTA: Domain-Adversarial Test-Time Adaptation for Cross-Domain WiFi-Based Human Activity RecognitionCode1
Autoregressive Adaptive Hypergraph Transformer for Skeleton-based Activity RecognitionCode1
TASAR: Transfer-based Attack on Skeletal Action RecognitionCode1
Skeleton-based Group Activity Recognition via Spatial-Temporal Panoramic GraphCode1
Comparing Self-Supervised Learning Techniques for Wearable Human Activity RecognitionCode1
IMUGPT 2.0: Language-Based Cross Modality Transfer for Sensor-Based Human Activity RecognitionCode1
A Review of Deep Learning Methods for Photoplethysmography DataCode1
Challenges in Multi-centric Generalization: Phase and Step Recognition in Roux-en-Y Gastric Bypass SurgeryCode1
Deep Unsupervised Domain Adaptation for Time Series Classification: a BenchmarkCode1
Multi-stage Learning for Radar Pulse Activity SegmentationCode1
Online Semi-Supervised Learning of Composite Event Rules by Combining Structure and Mass-Based Predicate SimilarityCode1
Navigating Open Set Scenarios for Skeleton-based Action RecognitionCode1
Action-slot: Visual Action-centric Representations for Multi-label Atomic Activity Recognition in Traffic ScenesCode1
Temporal Action Localization for Inertial-based Human Activity RecognitionCode1
Quantized Distillation: Optimizing Driver Activity Recognition Models for Resource-Constrained EnvironmentsCode1
Optimization-Free Test-Time Adaptation for Cross-Person Activity RecognitionCode1
Finding Order in Chaos: A Novel Data Augmentation Method for Time Series in Contrastive LearningCode1
Human Activity Segmentation Challenge @ ECML/PKDD’23Code1
Hard No-Box Adversarial Attack on Skeleton-Based Human Action Recognition with Skeleton-Motion-Informed GradientCode1
milliFlow: Scene Flow Estimation on mmWave Radar Point Cloud for Human Motion SensingCode1
Vision-Language Models can Identify Distracted Driver Behavior from Naturalistic VideosCode1
MultiWave: Multiresolution Deep Architectures through Wavelet Decomposition for Multivariate Time Series PredictionCode1
TS-MoCo: Time-Series Momentum Contrast for Self-Supervised Physiological Representation LearningCode1
Human skeletons and change detection for efficient violence detection in surveillance videosCode1
Exploring Few-Shot Adaptation for Activity Recognition on Diverse DomainsCode1
Generating Virtual On-body Accelerometer Data from Virtual Textual Descriptions for Human Activity RecognitionCode1
Time Series Segmentation Applied to a New Data Set for Mobile Sensing of Human ActivitiesCode1
Multimodal video and IMU kinematic dataset on daily life activities using affordable devices (VIDIMU)Code1
Dual-path Adaptation from Image to Video TransformersCode1
Towards Activated Muscle Group Estimation in the WildCode1
Deep Learning for Time Series Classification and Extrinsic Regression: A Current SurveyCode1
LaMPP: Language Models as Probabilistic Priors for Perception and ActionCode1
Towards Continual Egocentric Activity Recognition: A Multi-modal Egocentric Activity Dataset for Continual LearningCode1
Self-Supervised PPG Representation Learning Shows High Inter-Subject VariabilityCode1
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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