Gesture Recognition
62 papers with code • 12 benchmarks • 12 datasets
Gesture Recognition is an active field of research with applications such as automatic recognition of sign language, interaction of humans and robots or for new ways of controlling video games.
Source: Gesture Recognition in RGB Videos Using Human Body Keypoints and Dynamic Time Warping
Benchmarks
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Datasets
Aff-Wild
MSRC-12
SHREC
Florentine
MLGESTURE DATASET
TCG
Subtasks
Greatest papers with code
GesturePod: Enabling On-device Gesture-based Interaction for White Cane Users
Microsoft/EdgeML
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Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology (UIST'19) 2019
Our in-lab study shows that GesturePod achieves 92% gesture recognition accuracy and can help perform common smartphone tasks faster.
Ranked #1 on
Gesture Recognition
on GesturePod
XceptionTime: A Novel Deep Architecture based on Depthwise Separable Convolutions for Hand Gesture Classification
The proposed innovative XceptionTime is designed by integration of depthwise separable convolutions, adaptive average pooling, and a novel non-linear normalization technique.
Multivariate Time Series Classification with WEASEL+MUSE
patrickzib/SFA
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Multivariate time series (MTS) arise when multiple interconnected sensors record data over time.
Attention in Convolutional LSTM for Gesture Recognition
GuangmingZhu/AttentionConvLSTM
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NeurIPS 2018
On this basis, a new variant of LSTM is derived, in which the convolutional structures are only embedded into the input-to-state transition of LSTM.
Word-level Deep Sign Language Recognition from Video: A New Large-scale Dataset and Methods Comparison
Based on this new large-scale dataset, we are able to experiment with several deep learning methods for word-level sign recognition and evaluate their performances in large scale scenarios.
Unified Learning Approach for Egocentric Hand Gesture Recognition and Fingertip Detection
MahmudulAlam/Unified-Gesture-and-Fingertip-Detection
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The proposed algorithm uses a single convolutional neural network to predict the probabilities of finger class and positions of fingertips in one forward propagation.
Motion Fused Frames: Data Level Fusion Strategy for Hand Gesture Recognition
Acquiring spatio-temporal states of an action is the most crucial step for action classification.
Ranked #1 on
Hand Gesture Recognition
on ChaLean test
Neural Sign Language Translation
neccam/nslt
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CVPR 2018
SLR seeks to recognize a sequence of continuous signs but neglects the underlying rich grammatical and linguistic structures of sign language that differ from spoken language.
An Efficient PointLSTM for Point Clouds Based Gesture Recognition
Blueprintf/pointlstm-gesture-recognition-pytorch
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CVPR 2020
The proposed PointLSTM combines state information from neighboring points in the past with current features to update the current states by a weight-shared LSTM layer.
Ranked #1 on
Hand Gesture Recognition
on NVGesture
Fast and Robust Dynamic Hand Gesture Recognition via Key Frames Extraction and Feature Fusion
Gesture recognition is a hot topic in computer vision and pattern recognition, which plays a vitally important role in natural human-computer interface.
Ranked #1 on
Hand Gesture Recognition
on Cambridge