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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 401–410 of 1322 papers

Title	Date	Tasks	Status	Hype
Human Activity Behavioural Pattern Recognition in Smarthome with Long-hour Data Collection	Jun 23, 2023	Activity RecognitionHuman Activity Recognition	—Unverified	0
"Filling the Blanks'': Identifying Micro-activities that Compose Complex Human Activities of Daily Living	Jun 22, 2023	Activity RecognitionAttribute	—Unverified	0
MultiWave: Multiresolution Deep Architectures through Wavelet Decomposition for Multivariate Time Series Prediction	Jun 16, 2023	Activity RecognitionDeep Learning	CodeCode Available	1
Vision-Language Models can Identify Distracted Driver Behavior from Naturalistic Videos	Jun 16, 2023	Activity Recognition	CodeCode Available	1
DISC: a Dataset for Integrated Sensing and Communication in mmWave Systems	Jun 15, 2023	Activity RecognitionBenchmarking	—Unverified	0
TS-MoCo: Time-Series Momentum Contrast for Self-Supervised Physiological Representation Learning	Jun 10, 2023	Activity RecognitionClassification	CodeCode Available	1
Robust Explainer Recommendation for Time Series Classification	Jun 8, 2023	Activity RecognitionClassification	CodeCode Available	0
Neuro-Symbolic Approaches for Context-Aware Human Activity Recognition	Jun 8, 2023	Activity RecognitionHuman Activity Recognition	—Unverified	0
Towards Learning Discrete Representations via Self-Supervision for Wearables-Based Human Activity Recognition	Jun 1, 2023	Activity RecognitionHuman Activity Recognition	—Unverified	0
Unsupervised Statistical Feature-Guided Diffusion Model for Sensor-based Human Activity Recognition	May 30, 2023	Activity RecognitionGenerative Adversarial Network	—Unverified	0

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All datasets RWF-2000 Stanford40 First-Person Hand Action Benchmark Self-stimulatory Behavior Dataset

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Structured Keypoint Pooling	Accuracy	93.4	—	Unverified
2	Semi-Supervised Hard Attention (SSHA); pretrained on Deepmind Kinetics dataset	Accuracy	90.4	—	Unverified
3	Human Skeletons + Change Detection	Accuracy	90.25	—	Unverified
4	Separable Convolutional LSTM	Accuracy	89.75	—	Unverified
5	SPIL Convolution	Accuracy	89.3	—	Unverified
6	Flow Gated Network	Accuracy	87.25	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FocusCLIP	Top-3 Accuracy (%)	10.47	—	Unverified
2	CLIP	Top-3 Accuracy (%)	6.49	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Boutaleb et al.	1:1 Accuracy	97.91	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	all-landmark-model	Activity Recognition	0.76	—	Unverified