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 251–300 of 1322 papers

TitleStatusHype
Generalization Ability Analysis of Through-the-Wall Radar Human Activity Recognition—0
Understanding Human Activity with Uncertainty Measure for Novelty in Graph Convolutional Networks—0
WearableMil: An End-to-End Framework for Military Activity Recognition and Performance Monitoring—0
WiDistill: Distilling Large-scale Wi-Fi Datasets with Trajectory MatchingCode0
Does SpatioTemporal information benefit Two video summarization benchmarks?Code0
Plots Unlock Time-Series Understanding in Multimodal Models—0
TRIS-HAR: Transmissive Reconfigurable Intelligent Surfaces-assisted Cognitive Wireless Human Activity Recognition Using State Space Models—0
Deep Adversarial Learning with Activity-Based User Discrimination Task for Human Activity Recognition—0
Ranking the Top-K Realizations of Stochastically Known Event Logs—0
VecLSTM: Trajectory Data Processing and Management for Activity Recognition through LSTM Vectorization and Database Integration—0
Deep Heterogeneous Contrastive Hyper-Graph Learning for In-the-Wild Context-Aware Human Activity RecognitionCode0
Heterogeneous Hyper-Graph Neural Networks for Context-aware Human Activity Recognition—0
EAGLE: Egocentric AGgregated Language-video Engine—0
Non-stationary BERT: Exploring Augmented IMU Data For Robust Human Activity Recognition—0
Towards Child-Inclusive Clinical Video Understanding for Autism Spectrum Disorder—0
Context-Aware Predictive Coding: A Representation Learning Framework for WiFi SensingCode0
Multidimensional Human Activity Recognition With Large Language Model: A Conceptual Framework—0
Context-Aware Predictive Coding: A Representation Learning Framework for WiFi SensingCode0
Integrating Audio Narrations to Strengthen Domain Generalization in Multimodal First-Person Action Recognition—0
A Comprehensive Methodological Survey of Human Activity Recognition Across Divers Data Modalities—0
Language-centered Human Activity Recognition—0
Benchmarking 2D Egocentric Hand Pose Datasets—0
A Wearable Multi-Modal Edge-Computing System for Real-Time Kitchen Activity Recognition—0
Few-Shot Continual Learning for Activity Recognition in Classroom Surveillance Images—0
Unified Framework with Consistency across Modalities for Human Activity RecognitionCode0
A Critical Analysis on Machine Learning Techniques for Video-based Human Activity Recognition of Surveillance Systems: A Review—0
Robotic Vision and Multi-View Synergy: Action and activity recognition in assisted living scenariosCode0
Integrating Features for Recognizing Human Activities through Optimized Parameters in Graph Convolutional Networks and Transformer Architectures—0
TSAK: Two-Stage Semantic-Aware Knowledge Distillation for Efficient Wearable Modality and Model Optimization in Manufacturing Lines—0
Towards Battery-Free Wireless Sensing via Radio-Frequency Energy Harvesting—0
Towards Sustainable Personalized On-Device Human Activity Recognition with TinyML and Cloud-Enabled Auto Deployment—0
A Comparison of Deep Learning and Established Methods for Calf Behaviour MonitoringCode0
Explainable Deep Learning Framework for Human Activity Recognition—0
Generative AI based Secure Wireless Sensing for ISAC Networks—0
Limitations in Employing Natural Language Supervision for Sensor-Based Human Activity Recognition -- And Ways to Overcome Them—0
Action Recognition for Privacy-Preserving Ambient Assisted LivingCode0
Weak-Annotation of HAR Datasets using Vision Foundation ModelsCode0
MU-MAE: Multimodal Masked Autoencoders-Based One-Shot Learning—0
Adversarial Domain Adaptation for Cross-user Activity Recognition Using Diffusion-based Noise-centred LearningCode0
Enhancing Human Action Recognition and Violence Detection Through Deep Learning Audiovisual Fusion—0
A Tiny Supervised ODL Core with Auto Data Pruning for Human Activity Recognition—0
MPT-PAR:Mix-Parameters Transformer for Panoramic Activity Recognition—0
FedBChain: A Blockchain-enabled Federated Learning Framework for Improving DeepConvLSTM with Comparative Strategy InsightsCode0
Skeleton-Based Action Recognition with Spatial-Structural Graph ConvolutionCode0
Explainable Artificial Intelligence for Quantifying Interfering and High-Risk Behaviors in Autism Spectrum Disorder in a Real-World Classroom Environment Using Privacy-Preserving Video Analysis—0
ActivityCLIP: Enhancing Group Activity Recognition by Mining Complementary Information from Text to Supplement Image Modality—0
Babel: A Scalable Pre-trained Model for Multi-Modal Sensing via Expandable Modality Alignment—0
C3T: Cross-modal Transfer Through Time for Sensor-based Human Activity Recognition—0
Wallcamera: Reinventing the Wheel?—0
Probing Fine-Grained Action Understanding and Cross-View Generalization of Foundation Models—0
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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