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 91–100 of 1322 papers

Title	Date	Tasks	Status	Hype
Ego-Exo: Transferring Visual Representations from Third-person to First-person Videos	Apr 16, 2021	Activity RecognitionDiversity	CodeCode Available	1
SHARP: Environment and Person Independent Activity Recognition with Commodity IEEE 802.11 Access Points	Mar 17, 2021	Activity RecognitionBenchmarking	CodeCode Available	1
Interpretable Deep Learning for the Remote Characterisation of Ambulation in Multiple Sclerosis using Smartphones	Mar 16, 2021	Activity RecognitionHuman Activity Recognition	CodeCode Available	1
BASAR:Black-box Attack on Skeletal Action Recognition	Mar 9, 2021	Action RecognitionActivity Recognition	CodeCode Available	1
Hierarchical Self Attention Based Autoencoder for Open-Set Human Activity Recognition	Mar 7, 2021	Activity RecognitionDecoder	CodeCode Available	1
Efficient Two-Stream Network for Violence Detection Using Separable Convolutional LSTM	Feb 21, 2021	Activity RecognitionComputational Efficiency	CodeCode Available	1
SelfHAR: Improving Human Activity Recognition through Self-training with Unlabeled Data	Feb 11, 2021	Activity RecognitionData Augmentation	CodeCode Available	1
Human Activity Recognition using Wearable Sensors: Review, Challenges, Evaluation Benchmark	Jan 5, 2021	Activity RecognitionHuman Activity Recognition	CodeCode Available	1
Interactive Fusion of Multi-level Features for Compositional Activity Recognition	Dec 10, 2020	Action RecognitionActivity Recognition	CodeCode Available	1
Exploring Contrastive Learning in Human Activity Recognition for Healthcare	Nov 23, 2020	Activity RecognitionContrastive Learning	CodeCode Available	1

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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