Sign Language Recognition
Given a signed video input the task is to predict the (sequence of) sign(s) that are performed.
( Image credit: Word-level Deep Sign Language Recognition from Video: A New Large-scale Dataset and Methods Comparison )
Leaderboards
| TREND | DATASET | BEST METHOD | PAPER TITLE | PAPER | CODE | COMPARE |
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Greatest papers with code
Learning to Estimate 3D Hand Pose from Single RGB Images
ICCV 2017
• lmb-freiburg/hand3d
• 
Low-cost consumer depth cameras and deep learning have enabled reasonable 3D hand pose estimation from single depth images.
Neural Sign Language Translation
CVPR 2018
• neccam/nslt
•
SLR seeks to recognize a sequence of continuous signs but neglects the underlying rich grammatical and linguistic structures of sign language that differ from spoken language.
GESTURE RECOGNITION LANGUAGE MODELLING MACHINE TRANSLATION SIGN LANGUAGE RECOGNITION SIGN LANGUAGE TRANSLATION TOKENIZATION
SubUNets: End-To-End Hand Shape and Continuous Sign Language Recognition
We propose a novel deep learning approach to solve simultaneous alignment and recognition problems (referred to as "Sequence-to-sequence" learning).
Temporal Unet: Sample Level Human Action Recognition using WiFi
• geekfeiw/WiSLAR
• 
In this task, every WiFi distortion sample in the whole series should be categorized into one action, which is a critical technique in precise action localization, continuous action segmentation, and real-time action recognition.
SEMANTIC SEGMENTATION SIGN LANGUAGE RECOGNITION TEMPORAL ACTION LOCALIZATION
SignCol: Open-Source Software for Collecting Sign Language Gestures
Sign(ed) languages use gestures, such as hand or head movements, for communication.
Word-level Deep Sign Language Recognition from Video: A New Large-scale Dataset and Methods Comparison
Based on this new large-scale dataset, we are able to experiment with several deep learning methods for word-level sign recognition and evaluate their performances in large scale scenarios.