Gesture Recognition
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Subtasks
Greatest papers with code
GesturePod: Enabling On-device Gesture-based Interaction for White Cane Users
Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology (UIST'19) 2019
• Microsoft/EdgeML
• 
Our in-lab study shows that GesturePod achieves 92% gesture recognition accuracy and can help perform common smartphone tasks faster.
SOTA for Gesture Recognition on GesturePod
ASL Recognition with Metric-Learning based Lightweight Network
arXiv.org 2020
• opencv/openvino_training_extensions
• 
In the past decades the set of human tasks that are solved by machines was extended dramatically.
AUTONOMOUS DRIVING GESTURE RECOGNITION IMAGE CLASSIFICATION METRIC LEARNING SIGN LANGUAGE TRANSLATION
Multivariate Time Series Classification with WEASEL+MUSE
• patrickzib/SFA
•
Multivariate time series (MTS) arise when multiple interconnected sensors record data over time.
FEATURE SELECTION GESTURE RECOGNITION TIME SERIES TIME SERIES CLASSIFICATION
Attention in Convolutional LSTM for Gesture Recognition
NeurIPS 2018
• GuangmingZhu/AttentionConvLSTM
•
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.
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.
ACTION CLASSIFICATION HAND GESTURE RECOGNITION HAND-GESTURE RECOGNITION
Neural Sign Language Translation
CVPR 2018
• neccam/nslt
•
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.
#2 best model for
Sign Language Translation
on RWTH-PHOENIX-Weather 2014 T
GESTURE RECOGNITION LANGUAGE MODELLING MACHINE TRANSLATION SIGN LANGUAGE RECOGNITION SIGN LANGUAGE TRANSLATION TOKENIZATION
Recognizing Surgical Activities with Recurrent Neural Networks
• rdipietro/miccai-2016-surgical-activity-rec
•
In contrast, we work on recognizing both gestures and longer, higher-level activites, or maneuvers, and we model the mapping from kinematics to gestures/maneuvers with recurrent neural networks.
Deep Learning for Electromyographic Hand Gesture Signal Classification Using Transfer Learning
• UlysseCoteAllard/MyoArmbandDataset
•
Consequently, this paper proposes applying transfer learning on aggregated data from multiple users, while leveraging the capacity of deep learning algorithms to learn discriminant features from large datasets.
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.
Construct Dynamic Graphs for Hand Gesture Recognition via Spatial-Temporal Attention
We propose a Dynamic Graph-Based Spatial-Temporal Attention (DG-STA) method for hand gesture recognition.
SOTA for Hand Gesture Recognition on DHG-14