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 31–40 of 1322 papers

Title	Date	Tasks	Status	Hype
Quantized Distillation: Optimizing Driver Activity Recognition Models for Resource-Constrained Environments	Nov 10, 2023	Activity RecognitionAutonomous Driving	CodeCode Available	1
Optimization-Free Test-Time Adaptation for Cross-Person Activity Recognition	Oct 28, 2023	Activity RecognitionComputational Efficiency	CodeCode Available	1
Finding Order in Chaos: A Novel Data Augmentation Method for Time Series in Contrastive Learning	Sep 23, 2023	Activity RecognitionContrastive Learning	CodeCode Available	1
Human Activity Segmentation Challenge @ ECML/PKDD’23	Sep 18, 2023	Activity RecognitionChange Point Detection	CodeCode Available	1
Hard No-Box Adversarial Attack on Skeleton-Based Human Action Recognition with Skeleton-Motion-Informed Gradient	Aug 10, 2023	Action RecognitionActivity Recognition	CodeCode Available	1
milliFlow: Scene Flow Estimation on mmWave Radar Point Cloud for Human Motion Sensing	Jun 29, 2023	Activity RecognitionDecision Making	CodeCode Available	1
MultiWave: Multiresolution Deep Architectures through Wavelet Decomposition for Multivariate Time Series Prediction	Jun 16, 2023	Activity RecognitionDeep Learning	CodeCode Available	1
Vision-Language Models can Identify Distracted Driver Behavior from Naturalistic Videos	Jun 16, 2023	Activity Recognition	CodeCode Available	1
TS-MoCo: Time-Series Momentum Contrast for Self-Supervised Physiological Representation Learning	Jun 10, 2023	Activity RecognitionClassification	CodeCode Available	1
Human skeletons and change detection for efficient violence detection in surveillance videos	May 20, 2023	Activity RecognitionChange Detection	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