Gesture Recognition
115 papers with code • 13 benchmarks • 14 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
Libraries
Use these libraries to find Gesture Recognition models and implementationsDatasets
Latest papers with no code
An Evolutionary Network Architecture Search Framework with Adaptive Multimodal Fusion for Hand Gesture Recognition
To automatically adapt to various datasets, the ENAS framework is designed to automatically search a MHGR network with appropriate fusion positions and ratios.
Agile gesture recognition for low-power applications: customisation for generalisation
Automated hand gesture recognition has long been a focal point in the AI community.
A Simple Baseline for Efficient Hand Mesh Reconstruction
3D hand pose estimation has found broad application in areas such as gesture recognition and human-machine interaction tasks.
High-speed Low-consumption sEMG-based Transient-state micro-Gesture Recognition
The accuracy of the proposed SNN is 83. 85% and 93. 52% on the two datasets respectively.
Radar-Based Recognition of Static Hand Gestures in American Sign Language
This emphasizes the practicality of our methodology in overcoming data scarcity challenges and advancing the field of automatic gesture recognition in VR and HCI applications.
Hand Shape and Gesture Recognition using Multiscale Template Matching, Background Subtraction and Binary Image Analysis
This paper presents a hand shape classification approach employing multiscale template matching.
Spiking Neural Network Enhanced Hand Gesture Recognition Using Low-Cost Single-photon Avalanche Diode Array
We present a compact spiking convolutional neural network (SCNN) and spiking multilayer perceptron (SMLP) to recognize ten different gestures in dark and bright light environments, using a $9. 6 single-photon avalanche diode (SPAD) array.
Phase-driven Domain Generalizable Learning for Nonstationary Time Series
Monitoring and recognizing patterns in continuous sensing data is crucial for many practical applications.
ALERT-Transformer: Bridging Asynchronous and Synchronous Machine Learning for Real-Time Event-based Spatio-Temporal Data
We propose a novel hybrid pipeline composed of asynchronous sensing and synchronous processing that combines several ideas: (1) an embedding based on PointNet models -- the ALERT module -- that can continuously integrate new and dismiss old events thanks to a leakage mechanism, (2) a flexible readout of the embedded data that allows to feed any downstream model with always up-to-date features at any sampling rate, (3) exploiting the input sparsity in a patch-based approach inspired by Vision Transformer to optimize the efficiency of the method.
Efficient Gesture Recognition on Spiking Convolutional Networks Through Sensor Fusion of Event-Based and Depth Data
As intelligent systems become increasingly important in our daily lives, new ways of interaction are needed.