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 121–130 of 1322 papers

Title	Date	Tasks	Status	Hype	Score
Finding Order in Chaos: A Novel Data Augmentation Method for Time Series in Contrastive Learning	Sep 23, 2023	Activity RecognitionContrastive Learning	CodeCode Available	1	5
Vision-Language Models can Identify Distracted Driver Behavior from Naturalistic Videos	Jun 16, 2023	Activity Recognition	CodeCode Available	1	5
Quantized Distillation: Optimizing Driver Activity Recognition Models for Resource-Constrained Environments	Nov 10, 2023	Activity RecognitionAutonomous Driving	CodeCode Available	1	5
Generalized Relevance Learning Grassmann Quantization	Mar 14, 2024	Activity RecognitionFace Recognition	CodeCode Available	0	5
Fully Convolutional Network Bootstrapped by Word Encoding and Embedding for Activity Recognition in Smart Homes	Dec 1, 2020	Activity RecognitionGeneral Classification	CodeCode Available	0	5
An IoT Based Framework For Activity Recognition Using Deep Learning Technique	Jun 17, 2019	Activity RecognitionHuman Activity Recognition	CodeCode Available	0	5
FAR: Fourier Aerial Video Recognition	Mar 21, 2022	Action RecognitionActivity Recognition	CodeCode Available	0	5
Generative Pretrained Embedding and Hierarchical Irregular Time Series Representation for Daily Living Activity Recognition	Dec 27, 2024	Activity RecognitionDecoder	CodeCode Available	0	5
FedAli: Personalized Federated Learning with Aligned Prototypes through Optimal Transport	Nov 15, 2024	Activity RecognitionFederated Learning	CodeCode Available	0	5
An Interactive Greedy Approach to Group Sparsity in High Dimensions	Jul 10, 2017	Activity RecognitionHuman Activity Recognition	CodeCode Available	0	5

Show:10 25 50

← PrevPage 13 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