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 181–190 of 1322 papers

TitleStatusHype
Hybrid CNN-Dilated Self-attention Model Using Inertial and Body-Area Electrostatic Sensing for Gym Workout Recognition, Counting, and User AuthentificationCode0
Exploring FMCW Radars and Feature Maps for Activity Recognition: A Benchmark Study—0
CADDI: An in-Class Activity Detection Dataset using IMU data from low-cost sensors—0
SHADE-AD: An LLM-Based Framework for Synthesizing Activity Data of Alzheimer's Patients—0
FinP: Fairness-in-Privacy in Federated Learning by Addressing Disparities in Privacy Risk—0
GNN-XAR: A Graph Neural Network for Explainable Activity Recognition in Smart Homes—0
Random Projections and Natural Sparsity in Time-Series Classification: A Theoretical Analysis—0
On Neural Inertial Classification Networks for Pedestrian Activity Recognition—0
Enhancing Smart Environments with Context-Aware Chatbots using Large Language Models—0
Multi-view Video-Pose Pretraining for Operating Room Surgical 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