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 71–80 of 1322 papers

Title	Date	Tasks	Status	Hype	Score
A Federated Learning Aggregation Algorithm for Pervasive Computing: Evaluation and Comparison	Oct 19, 2021	Activity RecognitionFederated Learning	CodeCode Available	1	5
Exploring Few-Shot Adaptation for Activity Recognition on Diverse Domains	May 15, 2023	Action RecognitionActivity Recognition	CodeCode Available	1	5
Fine-Grained Egocentric Hand-Object Segmentation: Dataset, Model, and Applications	Aug 7, 2022	Activity RecognitionData Augmentation	CodeCode Available	1	5
Generating Virtual On-body Accelerometer Data from Virtual Textual Descriptions for Human Activity Recognition	May 4, 2023	Activity RecognitionHuman Activity Recognition	CodeCode Available	1	5
Hard No-Box Adversarial Attack on Skeleton-Based Human Action Recognition with Skeleton-Motion-Informed Gradient	Aug 10, 2023	Action RecognitionActivity Recognition	CodeCode Available	1	5
CALDA: Improving Multi-Source Time Series Domain Adaptation with Contrastive Adversarial Learning	Sep 30, 2021	Activity RecognitionContrastive Learning	CodeCode Available	1	5
Action-slot: Visual Action-centric Representations for Multi-label Atomic Activity Recognition in Traffic Scenes	Nov 29, 2023	Action RecognitionActivity Recognition	CodeCode Available	1	5
HHAR-net: Hierarchical Human Activity Recognition using Neural Networks	Oct 28, 2020	Activity RecognitionHuman Activity Recognition	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
Exploring Contrastive Learning in Human Activity Recognition for Healthcare	Nov 23, 2020	Activity RecognitionContrastive Learning	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