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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 276–300 of 572 papers

TitleStatusHype
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
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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