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 101–110 of 1322 papers

Title	Date	Tasks	Status	Hype	Score
Classification of Abnormal Hand Movement for Aiding in Autism Detection: Machine Learning Study	Aug 18, 2021	Action DetectionActivity Detection	CodeCode Available	1	5
Privacy and Utility Preserving Sensor-Data Transformations	Nov 14, 2019	Activity Recognition	CodeCode Available	1	5
3D Human Shape and Pose from a Single Low-Resolution Image with Self-Supervised Learning	Jul 27, 2020	3D Human Pose Estimation3D Shape Reconstruction	CodeCode Available	1	5
HAR-GCNN: Deep Graph CNNs for Human Activity Recognition From Highly Unlabeled Mobile Sensor Data	Mar 7, 2022	Activity RecognitionHuman Activity Recognition	CodeCode Available	1	5
Deep Unsupervised Domain Adaptation for Time Series Classification: a Benchmark	Dec 15, 2023	Activity RecognitionDomain Adaptation	CodeCode Available	1	5
DeepSense: A Unified Deep Learning Framework for Time-Series Mobile Sensing Data Processing	Nov 7, 2016	Activity RecognitionGeneral Classification	CodeCode Available	1	5
RF-Net: a Unified Meta-learning Framework for RF-enabled One-shot Human Activity Recognition	Oct 29, 2021	Activity RecognitionHuman Activity Recognition	CodeCode Available	1	5
SeCo: Exploring Sequence Supervision for Unsupervised Representation Learning	Aug 3, 2020	Action RecognitionActivity Recognition	CodeCode Available	1	5
Interactive Fusion of Multi-level Features for Compositional Activity Recognition	Dec 10, 2020	Action RecognitionActivity Recognition	CodeCode Available	1	5
NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding	May 12, 2019	Action RecognitionActivity Recognition	CodeCode Available	1	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