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 161–170 of 1322 papers

Title	Date	Tasks	Status
An Activity Recognition Framework for Continuous Monitoring of Non-Steady-State Locomotion of Individuals with Parkinson's Disease	Oct 8, 2021	Activity Recognition	—Unverified
A Multi-Task Deep Learning Approach for Sensor-based Human Activity Recognition and Segmentation	Mar 20, 2023	Activity RecognitionBenchmarking	—Unverified
Activity recognition from videos with parallel hypergraph matching on GPUs	May 4, 2015	Activity RecognitionGPU	—Unverified
A Multi-Stream Convolutional Neural Network Framework for Group Activity Recognition	Dec 26, 2018	Activity RecognitionGroup Activity Recognition	—Unverified
A Multi-Modal Explainability Approach for Human-Aware Robots in Multi-Party Conversation	May 20, 2024	Activity RecognitionBinary Classification	—Unverified
Activity Recognition From Newborn Resuscitation Videos	Mar 14, 2023	Activity Recognitionobject-detection	—Unverified
Automated Surgical Activity Recognition with One Labeled Sequence	Jul 20, 2019	Activity Recognition	—Unverified
A MIMO Radar-Based Metric Learning Approach for Activity Recognition	Nov 2, 2021	Activity RecognitionFew-Shot Learning	—Unverified
Am I fit for this physical activity? Neural embedding of physical conditioning from inertial sensors	Mar 22, 2021	Activity RecognitionHuman Activity Recognition	—Unverified
"Filling the Blanks'': Identifying Micro-activities that Compose Complex Human Activities of Daily Living	Jun 22, 2023	Activity RecognitionAttribute	—Unverified

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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