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Hand Gesture Recognition
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Hand gesture recognition (HGR) is a subarea of Computer Vision where the focus is on classifying a video or image containing a dynamic or static, respectively, hand gesture. In the static case, gestures are also generally called poses. HGR can also be performed with point cloud or joint hand data.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
TENNs-PLEIADES: Building Temporal Kernels with Orthogonal Polynomials
GestFormer: Multiscale Wavelet Pooling Transformer Network for Dynamic Hand Gesture Recognition
Wearable Sensor-Based Few-Shot Continual Learning on Hand Gestures for Motor-Impaired Individuals via Latent Embedding Exploitation
MEET: Mixture of Experts Extra Tree-Based sEMG Hand Gesture Identification
Stream State-tying for Sign Language Recognition
Pose2Gest: A Few-Shot Model-Free Approach Applied In South Indian Classical Dance Gesture Recognition
Towards Robust and Interpretable EMG-based Hand Gesture Recognition using Deep Metric Meta Learning
Optimizing the Deployment of Tiny Transformers on Low-Power MCUs
An Evolutionary Network Architecture Search Framework with Adaptive Multimodal Fusion for Hand Gesture Recognition
Agile gesture recognition for low-power applications: customisation for generalisation
Radar-Based Recognition of Static Hand Gestures in American Sign Language
Spiking Neural Network Enhanced Hand Gesture Recognition Using Low-Cost Single-photon Avalanche Diode Array
Resource-Efficient Gesture Recognition using Low-Resolution Thermal Camera via Spiking Neural Networks and Sparse Segmentation
EMG subspace alignment and visualization for cross-subject hand gesture classification
Improving Unimodal Inference with Multimodal Transformers
CASTER: A Computer-Vision-Assisted Wireless Channel Simulator for Gesture Recognition
Hand Gesture Classification on Praxis Dataset: Trading Accuracy for Expense
Handshape recognition for Argentinian Sign Language using ProbSom
GRLib: An Open-Source Hand Gesture Detection and Recognition Python Library
It's all about you: Personalized in-Vehicle Gesture Recognition with a Time-of-Flight Camera
A Deep Learning Sequential Decoder for Transient High-Density Electromyography in Hand Gesture Recognition Using Subject-Embedded Transfer Learning
EMGTFNet: Fuzzy Vision Transformer to decode Upperlimb sEMG signals for Hand Gestures Recognition
Dynamic Hand Gesture-Featured Human Motor Adaptation in Tool Delivery using Voice Recognition
Hand Gesture Recognition with Two Stage Approach Using Transfer Learning and Deep Ensemble Learning
On-device Real-time Custom Hand Gesture Recognition
From Unimodal to Multimodal: improving sEMG-Based Pattern Recognition via deep generative models
sEMG-based Hand Gesture Recognition with Deep Learning
CaptAinGlove: Capacitive and Inertial Fusion-Based Glove for Real-Time on Edge Hand Gesture Recognition for Drone Control
Agile gesture recognition for capacitive sensing devices: adapting on-the-job
Improving Rating Prediction in Multi-Criteria Recommender Systems via a Collective Factor Model
SimplyMime: A Control at Our Fingertips
OO-dMVMT: A Deep Multi-view Multi-task Classification Framework for Real-time 3D Hand Gesture Classification and Segmentation
PixelRNN: In-pixel Recurrent Neural Networks for End-to-end-optimized Perception with Neural Sensors
Deploying Machine Learning Models to Ahead-of-Time Runtime on Edge Using MicroTVM
IMU-based Modularized Wearable Device for Human Motion Classification
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.