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 1211–1220 of 1322 papers

Title	Date	Tasks	Status
Conditional-UNet: A Condition-aware Deep Model for Coherent Human Activity Recognition From Wearables	Apr 15, 2020	Activity RecognitionGesture Recognition	—Unverified
Contact-Free Multi-Target Tracking Using Distributed Massive MIMO-OFDM Communication System: Prototype and Analysis	Aug 23, 2022	Activity RecognitionCompressive Sensing	—Unverified
Contactless Human Activity Recognition using Deep Learning with Flexible and Scalable Software Define Radio	Apr 18, 2023	Activity RecognitionHuman Activity Recognition	—Unverified
Context Aware Active Learning of Activity Recognition Models	Dec 1, 2015	Active LearningActivity Recognition	—Unverified
Context Aware Group Activity Recognition	Jan 1, 2021	Activity RecognitionGroup Activity Recognition	—Unverified
Context-Aware Query Selection for Active Learning in Event Recognition	Apr 9, 2019	Active LearningActivity Recognition	—Unverified
Context-driven Active and Incremental Activity Recognition	Jun 7, 2019	Active LearningActivity Recognition	—Unverified
ContextGPT: Infusing LLMs Knowledge into Neuro-Symbolic Activity Recognition Models	Mar 11, 2024	Activity RecognitionCommon Sense Reasoning	—Unverified
Contextual Relationship-based Activity Segmentation on an Event Stream in the IoT Environment with Multi-user Activities	Sep 20, 2016	Activity RecognitionHuman Activity Recognition	—Unverified
Continual Learning for Multivariate Time Series Tasks with Variable Input Dimensions	Mar 14, 2022	Activity RecognitionContinual Learning	—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