https://github.com/ahmetgunduz/Real-time-GesRec
공식 코드Real-time Hand Gesture Detection and Classification Using Convolutional Neural Networks
Papers with Code 아카이브
Gesture Recognition
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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
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ai-forever/dynamic_gestures
공식 코드HaGRIDv2: 1M Images for Static and Dynamic Hand Gesture Recognition
https://github.com/aiotgroup/uwash
공식 코드You Can Wash Hands Better: Accurate Daily Handwashing Assessment with a Smartwatch
https://github.com/albertomarchisio/EfficientSNN
공식 코드https://github.com/albertosabater/eventtransformer
공식 코드Event Transformer. A sparse-aware solution for efficient event data processing
https://github.com/amr-gomaa/ML-PersRef
공식 코드https://github.com/amrgomaaelhady/synthogestures
공식 코드https://github.com/asankagp/UAV-GESTURE
공식 코드UAV-GESTURE: A Dataset for UAV Control and Gesture Recognition
https://github.com/chenxinyan-sg/wifi-csi-sensing-benchmark
공식 코드SenseFi: A Library and Benchmark on Deep-Learning-Empowered WiFi Human Sensing
https://github.com/cruiseresearchgroup/ESPRESSO
공식 코드ESPRESSO: Entropy and ShaPe awaRe timE-Series SegmentatiOn for processing heterogeneous sensor data
https://github.com/damo-cv/motionrgbd
공식 코드Decoupling and Recoupling Spatiotemporal Representation for RGB-D-based Motion Recognition
https://github.com/ds-hub-sochi/sl-techreport
공식 코드Fine-tuning of sign language recognition models: a technical report
https://github.com/dxli94/WLASL
공식 코드https://github.com/exoskelebox/force-myography-hand-gesture-recognition-benchmark-data
공식 코드Force myography benchmark data for hand gesture recognition and transfer learning
https://github.com/fandulu/DD-Net
공식 코드Make Skeleton-based Action Recognition Model Smaller, Faster and Better
https://github.com/feichtenhofer/twostreamfusion
공식 코드Two-Stream Convolutional Networks for Action Recognition in Videos
https://github.com/gauthamkrishna-g/Dynamic-Gesture-Recognition
공식 코드A Generic Multi-modal Dynamic Gesture Recognition System using Machine Learning
https://github.com/guoweiyu/spgesture
공식 코드https://github.com/hasanssl/bdslw60_code
공식 코드https://github.com/hassanali-90/snapture
공식 코드Snapture -- A Novel Neural Architecture for Combined Static and Dynamic Hand Gesture Recognition
https://github.com/holzbock/st_mlp
공식 코드A Spatio-Temporal Multilayer Perceptron for Gesture Recognition
https://github.com/homer-robotics/gesture_recognition_on_rgb_video
공식 코드Gesture Recognition in RGB Videos UsingHuman Body Keypoints and Dynamic Time Warping
https://github.com/hukenovs/hagrid
공식 코드https://github.com/intelligent-microsystems-lab/snnquantprune
공식 코드The Hardware Impact of Quantization and Pruning for Weights in Spiking Neural Networks
https://github.com/intelligolabs/oo-dmvmt
공식 코드https://github.com/jinbowen00/gda-for-wi-fi-gesture-recognization
공식 코드Generative AI for Data Augmentation in Wireless Networks: Analysis, Applications, and Case Study
https://github.com/josephsdavid/semg_repro
공식 코드https://github.com/kenshohara/3D-ResNets
공식 코드Learning Spatio-Temporal Features with 3D Residual Networks for Action Recognition
https://github.com/ketyi/2SRNN
공식 코드Domain Adaptation for sEMG-based Gesture Recognition with Recurrent Neural Networks
https://github.com/ketyi/Deep-2SRNN
공식 코드On the Metrics and Adaptation Methods for Domain Divergences of sEMG-based Gesture Recognition
https://github.com/khaleelkhan/evnn
공식 코드Efficient recurrent architectures through activity sparsity and sparse back-propagation through time
https://github.com/linuxsino/visual-text-mg
공식 코드https://github.com/lulucelia/SdConv
공식 코드Symmetric Dilated Convolution for Surgical Gesture Recognition
https://github.com/mallikagarg/convmixformer
공식 코드https://github.com/mallikagarg/gestformer
공식 코드GestFormer: Multiscale Wavelet Pooling Transformer Network for Dynamic Hand Gesture Recognition
https://github.com/mallikagarg/mvtn
공식 코드MVTN: A Multiscale Video Transformer Network for Hand Gesture Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.