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 571–580 of 1322 papers

Title	Date	Tasks	Status
Multimodal Generation of Novel Action Appearances for Synthetic-to-Real Recognition of Activities of Daily Living	Aug 3, 2022	Activity Recognitionmultimodal generation	CodeCode Available
Pose Uncertainty Aware Movement Synchrony Estimation via Spatial-Temporal Graph Transformer	Aug 1, 2022	Activity RecognitionContrastive Learning	—Unverified
Information We Can Extract About a User From 'One Minute Mobile Application Usage'	Jul 27, 2022	Activity Recognition	—Unverified
Domain Generalization for Activity Recognition via Adaptive Feature Fusion	Jul 21, 2022	Activity RecognitionDomain Adaptation	—Unverified
Discovering Behavioral Predispositions in Data to Improve Human Activity Recognition	Jul 18, 2022	Activity RecognitionHuman Activity Recognition	—Unverified
Using Anomaly Detection to Detect Poisoning Attacks in Federated Learning Applications	Jul 18, 2022	Activity RecognitionAnomaly Detection	—Unverified
Federated Self-Supervised Learning in Heterogeneous Settings: Limits of a Baseline Approach on HAR	Jul 17, 2022	Activity RecognitionFederated Learning	—Unverified
Federated Learning and catastrophic forgetting in pervasive computing: demonstration in HAR domain	Jul 17, 2022	Activity RecognitionFederated Learning	—Unverified
Federated Continual Learning through distillation in pervasive computing	Jul 17, 2022	Activity RecognitionContinual Learning	—Unverified
CHARM: A Hierarchical Deep Learning Model for Classification of Complex Human Activities Using Motion Sensors	Jul 16, 2022	Activity RecognitionHuman Activity Recognition	—Unverified

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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