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 71–80 of 1322 papers

Title	Date	Tasks	Status	Hype
TransDARC: Transformer-based Driver Activity Recognition with Latent Space Feature Calibration	Mar 2, 2022	Activity RecognitionHuman Activity Recognition	CodeCode Available	1
Wearable Sensor-Based Human Activity Recognition with Transformer Model	Mar 1, 2022	Activity RecognitionHuman Activity Recognition	CodeCode Available	1
Learning Disentangled Behaviour Patterns for Wearable-based Human Activity Recognition	Feb 15, 2022	Activity RecognitionDisentanglement	CodeCode Available	1
What Makes Good Contrastive Learning on Small-Scale Wearable-based Tasks?	Feb 12, 2022	Activity RecognitionContrastive Learning	CodeCode Available	1
COMPOSER: Compositional Reasoning of Group Activity in Videos with Keypoint-Only Modality	Dec 11, 2021	Activity RecognitionGroup Activity Recognition	CodeCode Available	1
PartImageNet: A Large, High-Quality Dataset of Parts	Dec 2, 2021	Activity RecognitionFew-Shot Learning	CodeCode Available	1
CubeLearn: End-to-end Learning for Human Motion Recognition from Raw mmWave Radar Signals	Nov 7, 2021	Activity Recognition	CodeCode Available	1
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
A Federated Learning Aggregation Algorithm for Pervasive Computing: Evaluation and Comparison	Oct 19, 2021	Activity RecognitionFederated Learning	CodeCode Available	1
OPERAnet: A Multimodal Activity Recognition Dataset Acquired from Radio Frequency and Vision-based Sensors	Oct 8, 2021	Activity RecognitionHuman Activity Recognition	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