SOTAVerified

Gesture Recognition

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

Papers

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Showing 401–450 of 572 papers

TitleStatusHype
Long-Distance Gesture Recognition using Dynamic Neural Networks—0
Low Power Neuromorphic EMG Gesture Classification—0
Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition—0
Making Convolutional Networks Recurrent for Visual Sequence Learning—0
Masked Autoencoder with Swin Transformer Network for Mitigating Electrode Shift in HD-EMG-based Gesture Recognition—0
Mediapipe and CNNs for Real-Time ASL Gesture Recognition—0
MEET: Mixture of Experts Extra Tree-Based sEMG Hand Gesture Identification—0
Memory-Efficient, Limb Position-Aware Hand Gesture Recognition using Hyperdimensional Computing—0
Micro Hand Gesture Recognition System Using Ultrasonic Active Sensing—0
Mining Limited Data Sufficiently: A BERT-inspired Approach for CSI Time Series Application in Wireless Communication and Sensing—0
ModDrop: adaptive multi-modal gesture recognition—0
MoEMba: A Mamba-based Mixture of Experts for High-Density EMG-based Hand Gesture Recognition—0
MoRSE: Deep Learning-based Arm Gesture Recognition for Search and Rescue Operations—0
Motion feature augmented network for dynamic hand gesture recognition from skeletal data—0
Motion Feature Augmented Recurrent Neural Network for Skeleton-based Dynamic Hand Gesture Recognition—0
MotionInput v2.0 supporting DirectX: A modular library of open-source gesture-based machine learning and computer vision methods for interacting and controlling existing software with a webcam—0
Multi-Label Class Balancing Algorithm for Action Unit Detection—0
Multimodal and self-supervised representation learning for automatic gesture recognition in surgical robotics—0
Multi-modal Fusion for Single-Stage Continuous Gesture Recognition—0
Multi-Modal Gesture Recognition from Video and Surgical Tool Pose Information via Motion Invariants—0
Multi-Modality Fusion based on Consensus-Voting and 3D Convolution for Isolated Gesture Recognition—0
Multiscaled Multi-Head Attention-based Video Transformer Network for Hand Gesture Recognition—0
Multi-Scale Spatial-Temporal Self-Attention Graph Convolutional Networks for Skeleton-based Action Recognition—0
Multi-Task and Multi-Modal Learning for RGB Dynamic Gesture Recognition—0
Multi-Task Recurrent Neural Network for Surgical Gesture Recognition and Progress Prediction—0
Multi-velocity neural networks for gesture recognition in videos—0
Natural Typing Recognition via Surface Electromyography—0
N-DriverMotion: Driver motion learning and prediction using an event-based camera and directly trained spiking neural networks on Loihi 2—0
Neural Network Based Lidar Gesture Recognition for Realtime Robot Teleoperation—0
Novel Human Machine Interface via Robust Hand Gesture Recognition System using Channel Pruned YOLOv5s Model—0
Object Recognition in Human Computer Interaction:- A Comparative Analysis—0
Object recognition through pose and shape estimation—0
On-device Real-time Custom Hand Gesture Recognition—0
On-device Real-time Hand Gesture Recognition—0
One for All: An End-to-End Compact Solution for Hand Gesture Recognition—0
One-Shot Federated Learning with Neuromorphic Processors—0
One-Shot-Learning Gesture Recognition using HOG-HOF Features—0
One Snapshot is All You Need: A Generalized Method for mmWave Signal Generation—0
One-Stage-TFS: Thai One-Stage Fingerspelling Dataset for Fingerspelling Recognition Frameworks—0
Online Detection and Classification of Dynamic Hand Gestures With Recurrent 3D Convolutional Neural Network—0
Online Few-shot Gesture Learning on a Neuromorphic Processor—0
Online Gesture Recognition using Transformer and Natural Language Processing—0
Online hand gesture recognition using Continual Graph Transformers—0
On the Pareto Efficiency of Quantized CNN—0
Open Access Dataset for Electromyography based Multi-code Biometric Authentication—0
Optical Wireless Communications: Enabling the Next Generation Network of Networks—0
Optimised Preprocessing for Automatic Mouth Gesture Classification—0
Passive Motion Detection via mmWave Communication System—0
Persistence-based Structural Recognition—0
Personalizing Gesture Recognition Using Hierarchical Bayesian Neural Networks—0
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All datasetsDVS128 GestureCapgMyo DB-aCapgMyo DB-bCapgMyo DB-cChaLearn 2013Chalearn 2014ChaLearn 2016GesturePodMontalbanoMSRC-12Ninapro DB-1 12 gesturesNinapro DB-1 8 gestures

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TENNs-PLEIADESAccuracy (%)100—Unverified
2mMND (BPTT)Accuracy (%)98—Unverified
3EGRUAccuracy (%)97.8—Unverified
4AlexNet+LSTMAccuracy (%)97.73—Unverified
5S-TLLRAccuracy (%)97.72—Unverified
6Event-SSMAccuracy (%)97.7—Unverified
7STL-SNNAccuracy (%)97.22—Unverified
8OTTTAccuracy (%)96.88—Unverified
9STS-ResNetAccuracy (%)96.7—Unverified
10mMND (STDP)Accuracy (%)96.6—Unverified
#ModelMetricClaimedVerifiedStatus
12SRNNAccuracy97.1—Unverified
#ModelMetricClaimedVerifiedStatus
12SRNNAccuracy97.1—Unverified
#ModelMetricClaimedVerifiedStatus
12SRNNAccuracy96.8—Unverified
#ModelMetricClaimedVerifiedStatus
13S Net TTMAccuracy92.08—Unverified
#ModelMetricClaimedVerifiedStatus
13D-CNN + LSTMAccuracy93.2—Unverified
#ModelMetricClaimedVerifiedStatus
13S Net TTMAccuracy39.95—Unverified
#ModelMetricClaimedVerifiedStatus
1GesturePodReal World Accuracy92—Unverified
#ModelMetricClaimedVerifiedStatus
1Temp Conv + LSTMError rate2.77—Unverified
#ModelMetricClaimedVerifiedStatus
13S Net TTMAccuracy99.01—Unverified
#ModelMetricClaimedVerifiedStatus
12SRNNAccuracy84.7—Unverified
#ModelMetricClaimedVerifiedStatus
12SRNNAccuracy90.7—Unverified
#ModelMetricClaimedVerifiedStatus
1PointLSTM14 gestures accuracy95.9—Unverified