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

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Showing 361–370 of 1322 papers

Title	Date	Tasks	Status
Post-train Black-box Defense via Bayesian Boundary Correction	Jun 29, 2023	Activity RecognitionAdversarial Attack	—Unverified
Attention-based Convolutional Neural Network for Weakly Labeled Human Activities Recognition with Wearable Sensors	Mar 24, 2019	Activity RecognitionHuman Activity Recognition	—Unverified
Discovering Behavioral Predispositions in Data to Improve Human Activity Recognition	Jul 18, 2022	Activity RecognitionHuman Activity Recognition	—Unverified
Description of Structural Biases and Associated Data in Sensor-Rich Environments	Apr 11, 2021	Activity Recognition	—Unverified
Design and Analysis of Efficient Attention in Transformers for Social Group Activity Recognition	Apr 15, 2024	Activity RecognitionGroup Activity Recognition	—Unverified
DeSPITE: Exploring Contrastive Deep Skeleton-Pointcloud-IMU-Text Embeddings for Advanced Point Cloud Human Activity Understanding	Jun 16, 2025	Activity RecognitionHuman Activity Recognition	—Unverified
Detecting Falls with X-Factor Hidden Markov Models	Apr 8, 2015	Activity RecognitionGeneral Classification	—Unverified
Detecting Intentions of Vulnerable Road Users Based on Collective Intelligence	Sep 11, 2018	Activity RecognitionIntent Detection	—Unverified
Detecting Unseen Falls from Wearable Devices using Channel-wise Ensemble of Autoencoders	Oct 12, 2016	Activity RecognitionOne-Class Classification	—Unverified
Disentangling Imperfect: A Wavelet-Infused Multilevel Heterogeneous Network for Human Activity Recognition in Flawed Wearable Sensor Data	Jan 26, 2024	Activity RecognitionHuman Activity Recognition	—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