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 581–590 of 1322 papers

Title	Date	Tasks	Status
Deep Generative Domain Adaptation with Temporal Attention for Cross-User Activity Recognition	Mar 12, 2024	Activity RecognitionDomain Adaptation	—Unverified
Deep Generative Domain Adaptation with Temporal Relation Knowledge for Cross-User Activity Recognition	Mar 12, 2024	Activity RecognitionDomain Adaptation	—Unverified
A Symbolic Representation of Human Posture for Interpretable Learning and Reasoning	Oct 17, 2022	Activity RecognitionSpatial Reasoning	—Unverified
AgentSense: Virtual Sensor Data Generation Using LLM Agents in Simulated Home Environments	Jun 13, 2025	Activity RecognitionHuman Activity Recognition	—Unverified
DeepCount: Crowd Counting with WiFi via Deep Learning	Mar 13, 2019	Activity RecognitionCrowd Counting	—Unverified
Deep, Convolutional, and Recurrent Models for Human Activity Recognition using Wearables	Apr 29, 2016	Activity RecognitionHuman Activity Recognition	—Unverified
A Survey on Multi-Resident Activity Recognition in Smart Environments	Apr 24, 2023	Activity RecognitionHuman Activity Recognition	—Unverified
Deep Auto-Set: A Deep Auto-Encoder-Set Network for Activity Recognition Using Wearables	Nov 20, 2018	Activity RecognitionMulti-class Classification	—Unverified
A Survey on Multimodal Wearable Sensor-based Human Action Recognition	Apr 14, 2024	Action RecognitionActivity Recognition	—Unverified
A framework for mining process models from emails logs	Sep 20, 2016	Activity Recognition	—Unverified

Show:10 25 50

← PrevPage 59 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