Sign Language Recognition
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Sign Language Recognition is a computer vision and natural language processing task that involves automatically recognizing and translating sign language gestures into written or spoken language. The goal of sign language recognition is to develop algorithms that can understand and interpret sign language, enabling people who use sign language as their primary mode of communication to communicate more easily with non-signers.
<span style="color:grey; opacity: 0.6">( Image credit: Word-level Deep Sign Language Recognition from Video: A New Large-scale Dataset and Methods Comparison )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/jackyjsy/CVPR21Chal-SLR
공식 코드https://github.com/jackyjsy/sam-slr-v2
공식 코드Sign Language Recognition via Skeleton-Aware Multi-Model Ensemble
https://github.com/jiafei127/cv_islr_www2025
공식 코드Exploiting Ensemble Learning for Cross-View Isolated Sign Language Recognition
https://github.com/kaistmm/SlowFastSign
공식 코드https://github.com/kayoyin/transformer-slt
공식 코드https://github.com/leekezar/improvingsignrecognitionwithphonology
공식 코드https://github.com/leekezar/semlex
공식 코드The Sem-Lex Benchmark: Modeling ASL Signs and Their Phonemes
https://github.com/lmb-freiburg/hand3d
공식 코드https://github.com/matyasbohacek/uwb-sl-wild
공식 코드Learning from What is Already Out There: Few-shot Sign Language Recognition with Online Dictionaries
https://github.com/mohaEs/SignCol
공식 코드SignCol: Open-Source Software for Collecting Sign Language Gestures
https://github.com/neccam/slt
공식 코드Sign Language Transformers: Joint End-to-end Sign Language Recognition and Translation
https://github.com/neilsong/slt
공식 코드SLGTformer: An Attention-Based Approach to Sign Language Recognition
https://github.com/nphamdinh/transfer-learning-vsr-mouthing-sign-language
공식 코드Transfer Learning from Visual Speech Recognition to Mouthing Recognition in German Sign Language
https://github.com/ntu-aiot/ObfNet
공식 코드Lightweight and Unobtrusive Data Obfuscation at IoT Edge for Remote Inference
https://github.com/oskoller/sign-language-state-of-the-art
공식 코드Quantitative Survey of the State of the Art in Sign Language Recognition
https://github.com/prasunroy/sign-language
공식 코드https://github.com/rtoengi/transfer-learning-for-sign-language-recognition
공식 코드https://github.com/s4nyam/pvt-addsl
공식 코드ADDSL: Hand Gesture Detection and Sign Language Recognition on Annotated Danish Sign Language
https://github.com/sakura2233565548/masa
공식 코드MASA: Motion-aware Masked Autoencoder with Semantic Alignment for Sign Language Recognition
https://github.com/sign-language-processing/mediapipe-hand-crop-fix
공식 코드https://github.com/snalyami/CLIP-SLA
공식 코드CLIP-SLA: Parameter-Efficient CLIP Adaptation for Continuous Sign Language Recognition
https://github.com/sutwangyan/MSKA
공식 코드Multi-Stream Keypoint Attention Network for Sign Language Recognition and Translation
https://github.com/suvajit-patra/sl-hwgat
공식 코드https://github.com/tinh2044/SignBart
공식 코드SignBart -- New approach with the skeleton sequence for Isolated Sign language Recognition
https://github.com/verashira/TSPNet
공식 코드TSPNet: Hierarchical Feature Learning via Temporal Semantic Pyramid for Sign Language Translation
https://github.com/woshisad159/tfnet
공식 코드A Chinese Continuous Sign Language Dataset Based on Complex Environments
https://github.com/ycmin95/VAC_CSLR
공식 코드Visual Alignment Constraint for Continuous Sign Language Recognition
https://github.com/yongcaoplus/tin-slt
공식 코드https://github.com/zechengli19/uni-sign
공식 코드Uni-Sign: Toward Unified Sign Language Understanding at Scale
https://github.com/zhoubenjia/gfslt-vlp
공식 코드Gloss-free Sign Language Translation: Improving from Visual-Language Pretraining
https://github.com/Chenzhoujia/190916-hand3d-CNN-GNN
https://github.com/OlineRanum/SAPA
https://github.com/OvrK12/slt
Sign Language Transformers: Joint End-to-end Sign Language Recognition and Translation
https://github.com/Sun1992/SSTCN-for-SLR
https://github.com/VNOpenAI/tf-blazepose
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.