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 731–740 of 1322 papers

Title	Date	Tasks	Status
Human Activity Recognition using Attribute-Based Neural Networks and Context Information	Oct 28, 2021	Activity RecognitionAttribute	—Unverified
International Workshop on Continual Semi-Supervised Learning: Introduction, Benchmarks and Baselines	Oct 27, 2021	Activity RecognitionCrowd Counting	—Unverified
Adversarial Deep Feature Extraction Network for User Independent Human Activity Recognition	Oct 23, 2021	Activity RecognitionDecoder	—Unverified
Domain Generalization through Audio-Visual Relative Norm Alignment in First Person Action Recognition	Oct 19, 2021	Action RecognitionActivity Recognition	—Unverified
A Survey of Human Activity Recognition in Smart Homes Based on IoT Sensors Algorithms: Taxonomies, Challenges, and Opportunities with Deep Learning	Oct 18, 2021	Activity RecognitionHuman Activity Recognition	—Unverified
Nuisance-Label Supervision: Robustness Improvement by Free Labels	Oct 14, 2021	Action RecognitionActivity Recognition	—Unverified
Tutorial on Deep Learning for Human Activity Recognition	Oct 13, 2021	Activity RecognitionDeep Learning	CodeCode Available
Guided-GAN: Adversarial Representation Learning for Activity Recognition with Wearables	Oct 12, 2021	Activity RecognitionGenerative Adversarial Network	—Unverified
An Activity Recognition Framework for Continuous Monitoring of Non-Steady-State Locomotion of Individuals with Parkinson's Disease	Oct 8, 2021	Activity Recognition	—Unverified
Cross-modal Knowledge Distillation for Vision-to-Sensor Action Recognition	Oct 8, 2021	Action RecognitionActivity Recognition	CodeCode Available

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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