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 421–430 of 1322 papers

Title	Date	Tasks	Status	Hype
Human skeletons and change detection for efficient violence detection in surveillance videos	May 20, 2023	Activity RecognitionChange Detection	CodeCode Available	1
Privacy in Multimodal Federated Human Activity Recognition	May 20, 2023	Activity RecognitionFederated Learning	—Unverified	0
Smart Pressure e-Mat for Human Sleeping Posture and Dynamic Activity Recognition	May 19, 2023	Activity Recognition	—Unverified	0
rWISDM: Repaired WISDM, a Public Dataset for Human Activity Recognition	May 17, 2023	Activity RecognitionHuman Activity Recognition	—Unverified	0
Exploring Few-Shot Adaptation for Activity Recognition on Diverse Domains	May 15, 2023	Action RecognitionActivity Recognition	CodeCode Available	1
A Matter of Annotation: An Empirical Study on In Situ and Self-Recall Activity Annotations from Wearable Sensors	May 15, 2023	Activity RecognitionHuman Activity Recognition	CodeCode Available	0
Is end-to-end learning enough for fitness activity recognition?	May 14, 2023	Action RecognitionActivity Recognition	—Unverified	0
Group Activity Recognition via Dynamic Composition and Interaction	May 9, 2023	Activity RecognitionGroup Activity Recognition	—Unverified	0
Distilled Mid-Fusion Transformer Networks for Multi-Modal Human Activity Recognition	May 5, 2023	Activity RecognitionFeature Engineering	—Unverified	0
Generating Virtual On-body Accelerometer Data from Virtual Textual Descriptions for Human Activity Recognition	May 4, 2023	Activity RecognitionHuman Activity Recognition	CodeCode Available	1

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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