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 621–630 of 1322 papers

Title	Date	Tasks	Status	Hype
Audio-Adaptive Activity Recognition Across Video Domains	Mar 27, 2022	Activity RecognitionDomain Adaptation	CodeCode Available	1
Knowledge Mining with Scene Text for Fine-Grained Recognition	Mar 27, 2022	Activity RecognitionClassification	CodeCode Available	1
Bridge-Prompt: Towards Ordinal Action Understanding in Instructional Videos	Mar 26, 2022	Action SegmentationAction Understanding	CodeCode Available	1
Seeker: Synergizing Mobile and Energy Harvesting Wearable Sensors for Human Activity Recognition	Mar 25, 2022	Activity RecognitionHuman Activity Recognition	—Unverified	0
EnHDC: Ensemble Learning for Brain-Inspired Hyperdimensional Computing	Mar 25, 2022	Activity RecognitionEnsemble Learning	—Unverified	0
Negative Selection by Clustering for Contrastive Learning in Human Activity Recognition	Mar 23, 2022	Activity RecognitionClustering	—Unverified	0
FAR: Fourier Aerial Video Recognition	Mar 21, 2022	Action RecognitionActivity Recognition	CodeCode Available	0
SemiPFL: Personalized Semi-Supervised Federated Learning Framework for Edge Intelligence	Mar 15, 2022	Activity RecognitionFederated Learning	CodeCode Available	1
Deep Transfer Learning with Graph Neural Network for Sensor-Based Human Activity Recognition	Mar 14, 2022	Activity RecognitionFew-Shot Learning	—Unverified	0
Continual Learning for Multivariate Time Series Tasks with Variable Input Dimensions	Mar 14, 2022	Activity RecognitionContinual Learning	—Unverified	0

Show:10 25 50

← PrevPage 63 of 133Next →

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