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

Showing 251300 of 1322 papers

TitleStatusHype
Cheating off your neighbors: Improving activity recognition through corroboration0
Anomaly detection and regime searching in fitness-tracker data0
Attend And Discriminate: Beyond the State-of-the-Art for Human Activity Recognition using Wearable Sensors0
An Empirical Study on Activity Recognition in Long Surgical Videos0
3D Human Activity Recognition with Reconfigurable Convolutional Neural Networks0
A Tree-structure Convolutional Neural Network for Temporal Features Exaction on Sensor-based Multi-resident Activity Recognition0
A Transformer-Based Model for the Prediction of Human Gaze Behavior on Videos0
A Heat-Map-based Algorithm for Recognizing Group Activities in Videos0
A Transfer Learning Method for Goal Recognition Exploiting Cross-Domain Spatial Features0
A Tiny Supervised ODL Core with Auto Data Pruning for Human Activity Recognition0
ActivityCLIP: Enhancing Group Activity Recognition by Mining Complementary Information from Text to Supplement Image Modality0
A Comparative Study of Human Activity Recognition: Motion, Tactile, and multi-modal Approaches0
Decoding Human Activities: Analyzing Wearable Accelerometer and Gyroscope Data for Activity Recognition0
Deep Adaptive Temporal Pooling for Activity Recognition0
AHAR: Adaptive CNN for Energy-efficient Human Activity Recognition in Low-power Edge Devices0
A systematic review of smartphone-based human activity recognition for health research0
A compact sequence encoding scheme for online human activity recognition in HRI applications0
AsyMov: Integrated Sensing and Communications with Asynchronous Moving Devices0
A Symbolic Representation of Human Posture for Interpretable Learning and Reasoning0
AgentSense: Virtual Sensor Data Generation Using LLM Agents in Simulated Home Environments0
A Survey on Multi-Resident Activity Recognition in Smart Environments0
A Survey on Multimodal Wearable Sensor-based Human Action Recognition0
A framework for mining process models from emails logs0
A Survey on Human-aware Robot Navigation0
A Survey of Knowledge Representation in Service Robotics0
A Framework For Identifying Group Behavior Of Wild Animals0
Activity-Aware Deep Cognitive Fatigue Assessment using Wearables0
Day2Dark: Pseudo-Supervised Activity Recognition beyond Silent Daylight0
A Survey of IMU Based Cross-Modal Transfer Learning in Human Activity Recognition0
A Fourier Domain Feature Approach for Human Activity Recognition & Fall Detection0
Multi-Modal Recognition of Worker Activity for Human-Centered Intelligent Manufacturing0
A Survey of Human Activity Recognition in Smart Homes Based on IoT Sensors Algorithms: Taxonomies, Challenges, and Opportunities with Deep Learning0
A Survey of Application of Machine Learning in Wireless Indoor Positioning Systems0
Affinity-Based Hierarchical Learning of Dependent Concepts for Human Activity Recognition0
Dataiku's Solution to SPHERE's Activity Recognition Challenge0
Integrated Human Activity Sensing and Communications0
Assessing the State of Self-Supervised Human Activity Recognition using Wearables0
Assessing the Impact of Sampling Irregularity in Time Series Data: Human Activity Recognition As A Case Study0
AssembleNet++: Assembling Modality Representations via Attention Connections - Supplementary Material -0
A Feature Selection Method for Multi-Dimension Time-Series Data0
A communication efficient distributed learning framework for smart environments0
Dataset Bias in Human Activity Recognition0
Decoding Children's Social Behavior0
Deep Adversarial Learning with Activity-Based User Discrimination Task for Human Activity Recognition0
CSI-Based Efficient Self-Quarantine Monitoring System Using Branchy Convolution Neural Network0
Adversarial Transferability in Wearable Sensor Systems0
A Semi-supervised Approach for Activity Recognition from Indoor Trajectory Data0
ARN-LSTM: A Multi-Stream Fusion Model for Skeleton-based Action Recognition0
ARIC: An Activity Recognition Dataset in Classroom Surveillance Images0
Arianna+: Scalable Human Activity Recognition by Reasoning with a Network of Ontologies0
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Benchmark Results

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