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 191–200 of 1322 papers

Title	Date	Tasks	Status	Score
Exploring Video-Based Driver Activity Recognition under Noisy Labels	Apr 16, 2025	Activity RecognitionDenoising	CodeCode Available	5
Enhancing Wearable Tap Water Audio Detection through Subclass Annotation in the HD-Epic Dataset	May 27, 2025	Activity RecognitionHuman Activity Recognition	CodeCode Available	5
Enhanced Spatio- Temporal Image Encoding for Online Human Activity Recognition	Dec 15, 2023	Activity RecognitionHuman Activity Recognition	CodeCode Available	5
Ensemble diverse hypotheses and knowledge distillation for unsupervised cross-subject adaptation	Apr 15, 2022	Activity RecognitionDomain Adaptation	CodeCode Available	5
A Matter of Annotation: An Empirical Study on In Situ and Self-Recall Activity Annotations from Wearable Sensors	May 15, 2023	Activity RecognitionHuman Activity Recognition	CodeCode Available	5
Human Activity Recognition Based on Wearable Sensor Data: A Standardization of the State-of-the-Art	Jun 13, 2018	Activity RecognitionHuman Activity Recognition	CodeCode Available	5
Eidetic 3D LSTM: A Model for Video Prediction and Beyond	May 1, 2019	Activity RecognitionVideo Prediction	CodeCode Available	5
Human Activity Recognition in an Open World	Dec 23, 2022	Activity RecognitionHuman Activity Recognition	CodeCode Available	5
Attention-Refined Unrolling for Sparse Sequential micro-Doppler Reconstruction	Jun 25, 2023	Activity Recognitioncompressed sensing	CodeCode Available	5
Dynamic Vision Sensors for Human Activity Recognition	Mar 13, 2018	Activity RecognitionHuman Activity Recognition	CodeCode Available	5

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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