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 41–50 of 1322 papers

Title	Date	Tasks	Status	Hype	Score
Classification of Abnormal Hand Movement for Aiding in Autism Detection: Machine Learning Study	Aug 18, 2021	Action DetectionActivity Detection	CodeCode Available	1	5
Deep Learning for Time Series Classification and Extrinsic Regression: A Current Survey	Feb 6, 2023	Activity RecognitionClassification	CodeCode Available	1	5
Dual-path Adaptation from Image to Video Transformers	Mar 17, 2023	Action ClassificationAction Recognition	CodeCode Available	1	5
Efficient Two-Stream Network for Violence Detection Using Separable Convolutional LSTM	Feb 21, 2021	Activity RecognitionComputational Efficiency	CodeCode Available	1	5
SHARP: Environment and Person Independent Activity Recognition with Commodity IEEE 802.11 Access Points	Mar 17, 2021	Activity RecognitionBenchmarking	CodeCode Available	1	5
ESPRESSO: Entropy and ShaPe awaRe timE-Series SegmentatiOn for processing heterogeneous sensor data	Jul 24, 2020	Activity RecognitionChange Point Detection	CodeCode Available	1	5
Bridge-Prompt: Towards Ordinal Action Understanding in Instructional Videos	Mar 26, 2022	Action SegmentationAction Understanding	CodeCode Available	1	5
A Review of Deep Learning Methods for Photoplethysmography Data	Jan 23, 2024	Activity RecognitionDeep Learning	CodeCode Available	1	5
Generating Virtual On-body Accelerometer Data from Virtual Textual Descriptions for Human Activity Recognition	May 4, 2023	Activity RecognitionHuman Activity Recognition	CodeCode Available	1	5
CALDA: Improving Multi-Source Time Series Domain Adaptation with Contrastive Adversarial Learning	Sep 30, 2021	Activity RecognitionContrastive Learning	CodeCode Available	1	5

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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