About
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 )
Benchmarks
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Datasets
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.
TSPNet: Hierarchical Feature Learning via Temporal Semantic Pyramid for Sign Language Translation
Sign language translation (SLT) aims to interpret sign video sequences into text-based natural language sentences.
SIGN LANGUAGE RECOGNITION SIGN LANGUAGE TRANSLATION VIDEO SEGMENTATION VIDEO SEMANTIC SEGMENTATION
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.
ACTION CLASSIFICATION HAND GESTURE RECOGNITION SIGN LANGUAGE RECOGNITION SIGN LANGUAGE TRANSLATION
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.
4 GESTURE RECOGNITION LANGUAGE MODELLING MACHINE TRANSLATION SIGN LANGUAGE RECOGNITION SIGN LANGUAGE TRANSLATION TOKENIZATION
Sign Language Transformers: Joint End-to-end Sign Language Recognition and Translation
CVPR 2020
• neccam/slt
• 
We report state-of-the-art sign language recognition and translation results achieved by our Sign Language Transformers.
4 SIGN LANGUAGE RECOGNITION SIGN LANGUAGE TRANSLATION TOKENIZATION
Better Sign Language Translation with STMC-Transformer
arXiv preprint 2020
• kayoyin/transformer-slt
•
This contradicts previous claims that GT gloss translation acts as an upper bound for SLT performance and reveals that glosses are an inefficient representation of sign language.
Ranked #1 on
Sign Language Translation
on ASLG-PC12
BlazePose: On-device Real-time Body Pose tracking
We present BlazePose, a lightweight convolutional neural network architecture for human pose estimation that is tailored for real-time inference on mobile devices.
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).
BSL-1K: Scaling up co-articulated sign language recognition using mouthing cues
Recent progress in fine-grained gesture and action classification, and machine translation, point to the possibility of automated sign language recognition becoming a reality.
ACTION CLASSIFICATION ACTION CLASSIFICATION KEYWORD SPOTTING MACHINE TRANSLATION SIGN LANGUAGE RECOGNITION
Fingerspelling recognition in the wild with iterative visual attention
ICCV 2019
• fmahoudeau/MiCT-RANet-ASL-FingerSpelling
•
In this paper we focus on recognition of fingerspelling sequences in American Sign Language (ASL) videos collected in the wild, mainly from YouTube and Deaf social media.