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 691–700 of 1322 papers

Title	Date	Tasks	Status	Hype
Nuisance-Label Supervision: Robustness Improvement by Free Labels	Oct 14, 2021	Action RecognitionActivity Recognition	—Unverified	0
Tutorial on Deep Learning for Human Activity Recognition	Oct 13, 2021	Activity RecognitionDeep Learning	CodeCode Available	0
Guided-GAN: Adversarial Representation Learning for Activity Recognition with Wearables	Oct 12, 2021	Activity RecognitionGenerative Adversarial Network	—Unverified	0
Cross-modal Knowledge Distillation for Vision-to-Sensor Action Recognition	Oct 8, 2021	Action RecognitionActivity Recognition	CodeCode Available	0
An Activity Recognition Framework for Continuous Monitoring of Non-Steady-State Locomotion of Individuals with Parkinson's Disease	Oct 8, 2021	Activity Recognition	—Unverified	0
OPERAnet: A Multimodal Activity Recognition Dataset Acquired from Radio Frequency and Vision-based Sensors	Oct 8, 2021	Activity RecognitionHuman Activity Recognition	CodeCode Available	1
Lightweight Transformer in Federated Setting for Human Activity Recognition	Oct 1, 2021	Activity RecognitionFederated Learning	—Unverified	0
CALDA: Improving Multi-Source Time Series Domain Adaptation with Contrastive Adversarial Learning	Sep 30, 2021	Activity RecognitionContrastive Learning	CodeCode Available	1
DIVERSIFY to Generalize: Learning Generalized Representations for Time Series Classification	Sep 29, 2021	Activity RecognitionClassification	—Unverified	0
T-WaveNet: A Tree-Structured Wavelet Neural Network for Time Series Signal Analysis	Sep 29, 2021	Activity RecognitionRepresentation Learning	—Unverified	0

Show:10 25 50

← PrevPage 70 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