Sign Language Recognition

Follow this topic Ask about this topic

Latest papers 55

6 papers in the last four weeks, down 33% on the four weeks before. 0.0% of all new papers.

All topics

A Hybrid Kinematic GCN and Elastic Transformer for Efficient Indian Sign Language Recognition
Oct 10, 2026Pushp Garg, Himangshu Sarma, Mrinmoy GhoraiSign Language Recognition Transformer
Human Computer Interaction Lab, IIIT SriCity, India
Machine Translation for Sign Languages
Oct 1, 2026Ozge Mercanoglu Sincan, Anton Pelykh, Edward Fish +7Sign Language Translation Sign Language Recognition
Centre for Vision, Speech and Signal Processing (CVSSP), University of Surrey, Guildford, UK, GU2 7XH.
OneSign: Unifying Sign Language Understanding Tasks with One Model
Sep 27, 2026Shiwei Gan, Yafeng Yin, Xiao Liu +3Sign Language Recognition Unified Multimodal Models
State Key Laboratory of Novel Software Technology, Nanjing University, Nanjing 210023, China
Seeing Semantic Shift: Difference-Aware Sentence-Level Temporal Segmentation of Sign Language Videos
Sep 25, 2026Bowen Guo, Shiwei Gan, Yafeng Yin +4Boundary-Aware Segmentation Temporal Action Segmentation
State Key Laboratory for Novel Software Technology, Nanjing University, Suzhou, China
Isolated Sign Language Recognition for Icelandic Sign Language: Experiments in a Low-resource Setting
Sep 22, 2026Finnur Ágúst Ingimundarson, Guðný Björk Þorvaldsdóttir, Mathias Müller +1Few-Shot Learning Sign Language Recognition
Department of Computational Linguistics, University of Zurich · Communication Centre for the Deaf and Hard of Hearing in Iceland
Zero-Shot Cross-Lingual Recognition of Sign Language Handshapes
Sep 16, 2026Marcel Granero-Moya, Carolina del Corral Farrarós, Gloria Haro +2Zero-Shot Learning Sign Language Recognition
Universitat Pompeu Fabra
Learning Sign Language Recognition under Label Noise: A Study of Noise-Robust Losses for Isolated and Continuous Settings
Sep 11, 2026Akihisa Shitara, Yoichi OchiaiNoisy-Label Learning Robust Loss Functions
R&D Center for Digital Nature, University of Tsukuba · Faculty of Library, Information and Media Science, University of Tsukuba · Pixie Dust Technologies, Inc.
RAIDAL: Redundancy-Aware Information Density Active Learning for CTC-Based Continuous Sign Language Recognition
Sep 6, 2026Rafael A. Diniz Augusto, Gabriel L. Oliveira, Erickson R. NascimentoActive Learning Sign Language Recognition
Universidade Federal de Minas Gerais Belo Horizonte, Minas Gerais, Brazil · University of Bristol Bristol, UK
SignDino: Self-Supervised Sign Language Representation Learning via Temporal-Axis Self-Distillation
Sep 5, 2026Junyi Hu, Zhewen He, Haomian Huang +3Self-Supervised Learning Sign Language Recognition
New York University Abu Dhabi
A Reverse Sign Language Dictionary: Open-Vocabulary Sign Recognition from Continuous Signing via Video Captioning and Description Retrieval
Sep 3, 2026Santiago Poveda-Gutiérrez, Hideki Nakayama, Mayumi BonoVideo Captioning Vision-Language Retrieval
Grad. School of IST The University of Tokyo Tokyo, Japan · Information and Society Research Division National Institute of Informatics Tokyo, Japan
SignSeek: Learning Transferable Representations for Sign Dictionary Retrieval
Sep 3, 2026Sobhan Asasi, Ozge Mercanoglu Sincan, Richard BowdenContrastive Learning Representation Learning
CVSSP, University of Surrey
SignMatch: Matching Dictionary Signs to Continuous Sign Language Video
Sep 1, 2026Ryan Wong, Youngjoon Jang, Liliane Momeni +2Sign Language Recognition
Visual Geometry Group Department of Engineering Science University of Oxford UK · LIGM, École des Ponts, IP Paris, Univ Gustave Eiffel, CNRS France
SMART: MLLM-guided Temporal Alignment for Unifying Sign Language Recognition and Spotting
Aug 26, 2026Eunjee Choi, JungHoon Sung, Seongwhan Cho +2Sign Language Recognition Vision-Language Alignment
Dankook University · Yongin, Korea
JSL-DC: A Word-Level Japanese Sign Language Dataset with Linguist-Derived Descriptions for Distinguishing Confusable Signs
Aug 19, 2026Ken Takaki, Asuka Ando, Misa Suzuki +12Sign Language Datasets Sign Language Recognition
The University of Tokyo · Independent · Kwansei Gakuin University +3
Cross-Sign Language Transfer Learning Using Domain Adaptation with Multi-scale Temporal Alignment
Aug 17, 2026Keren Artiaga, Yang Li, Ercan Engin Kuruoglu +2Sign Language Recognition Cross-Lingual Transfer
Victor · Tsinghua-Berkeley Shenzhen Insitute, Tsinghua Shenzhen International Graduate School, The University Town, Nanshan District, Shenzhen, 518055, P.R.China.
A HamNoSys-Guided Dataset and Baselines for Fine-Grained Isolated Handshape Recognition in Sign Language
Aug 11, 2026Ushnish Sarkar, Suvajit Patra, Bhaswar Chattopadhyay +2Sign Language Recognition Sign Language Datasets
Computer and Informatics Group, Variable Energy Cyclotron Centre, Kolkata, 700064, India. · Homi Bhabha National Institute, Mumbai, 400094, India. · Ramakrishna Mission Vivekananda Educational and Research Institute, Belur, 711202, India.
Sign Language Recognition Using Original and Synthetic Depth Image Based Point Cloud Data Models
Aug 10, 2026Rustem Ozakar, Eyup GedikliPoint Cloud Classification Sign Language Recognition
Department of Computer Engineering Erzurum Technical University Erzurum, Turkey · Department of Computer Engineering Trabzon University Trabzon, Turkey
Toward Deployable Bangla Sign Language Recognition with Expert-Validated Data and a Lightweight Attention-Based Model
Aug 6, 2026Saad Ahmed, Md Khalid SyfullahConvolutional Neural Networks Sign Language Recognition
Department of Computer Science and Engineering, Bangladesh Army University of Science and Technology, Saidpur Cantonment, Saidpur, Bangladesh
A Low-Cost Hybrid Reservoir Computing Model for Isolated Sign Language Video Recognition
Aug 4, 2026Nitin Kumar Singh, Arie Rachmad Syulistyo, Yuichiro Tanaka +1Reservoir Computing Sign Language Recognition
Woosong University Kazakhstan, Turkistan City, Kazakhstan · Data Science and Artificial Intelligence Laboratory (DSAIL), Woosong University Kazakhstan, Turkistan City, Kazakhstan · Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, 2-4 Hibikino, Wakamatsu, Kitakyushu, 808-0196, Japan +2
TransSLR: A Lightweight Transformer for Sign Language Recognition
Aug 3, 2026Lucia Yen Wanchi, Samuel Johnny, Victor Tolulope Olufemi +2Sign Language Recognition
Carnegie Mellon University Africa
Sign Language Question Answering: A New Task, Benchmark, and Baseline for Sign Language Understanding
Jul 30, 2026Shiwei Gan, Lichen Wang, Xiao Liu +4Sign Language Recognition Sign Language Datasets
State Key Laboratory of Novel Software Technology, Nanjing University, Nanjing 210023, China
The In-Car Sign Language Corpus (ICSL): A Multi-Modal Resource for Constrained-Space Sign Language Recognition
Jul 13, 2026Raviteja Boddu, Guilherme Vieira Leite, Joed Lopes da Silva +9Sign Language Recognition Sign Language Datasets
Technische Hochschule Ingolstadt (THI), Bayern, Germany · Universidade Estadual de Campinas (UNICAMP), São Paulo, Brazil · Universidade de São Paulo (USP), São Paulo, Brazil
Do Transformer Temporal Heads and Post-Pooling Motion Gates Help CorrNet-based CSLR? An Empirical Study
Jul 10, 2026Lisi Wang, Zhidong Xiao, Jianjun PengTransformer Sign Language Recognition
University of New South Wales, Sydney, Australia · National Centre for Computer Animation, Faculty of Media, Science and Technology, Bournemouth University, BH12 5BB, United Kingdom · School of Information Science and Engineering, Dalian Polytechnic University, Dalian 116034, China
Semantic Hardness Is Not Visual Hardness: Sign-Aware Hard Negative Mining for Sign Language Retrieval
Jul 10, 2026Junmyeong Lee, Chan Hur, ChangSu Choi +5Hard Negative Mining Cross-Modal Retrieval
School of Computing1 · ETRI Medical Informatics Laboratory4 · Graduate School of Culture Technology2 +1
Phonological Perception of Sign Language Models
Jun 27, 2026Kayo Yin, Jessica Carter, Alex Xijie Lu +1Sign Language Recognition Computational Psycholinguistics
University of California, Berkeley · Johns Hopkins University · Microsoft Research
SignNet-1M: Large-Scale Multilingual Sign Language Video Dataset with Downstream Benchmarks
Jun 23, 2026Zhewen He, Junyi Hu, Haomian Huang +3Distribution Shift Robustness Synthetic Data Augmentation
New York University Abu Dhabi, UAE · ChatSign Technology · Tsinghua University, China
Deep Learning-Based Sign Language Recognition from Videos and Cross-Lingual Translation to Indian Vernaculars
Jun 21, 2026Ramesh Nandipalli, Chandranath AdakSign Language Translation Sign Language Recognition
Department of Computer Science and Engineering, Indian Institute of Technology Patna, Bihar, India
SignVLA: Real-Time Sign Language-Guided Robotic Manipulation via Attention LSTM and Vision-Language-Action Models
Jun 18, 2026Ningwei Bai, Xinyu Tan, Harry Gardner +6Sign Language Translation Language-Conditioned Robot Manipulation
Department of Computer Science, University College London.
What's the Point? Spatial Grammar & Index Resolution for Sign Language Processing
Jun 6, 2026Oline Ranum, Simon Hadfield, Richard BowdenCoreference Resolution Sign Language Recognition
Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford, UK
SLU-2K: A Question-Based Benchmark for Semantic Evaluation of Sign Language Translation
Jun 2, 2026Zeno Testa, Antonino Furnari, Lorenzo Baraldi +1Sign Language Translation Video QA
University of Modena and Reggio Emilia Modena, Italy · University of Catania Catania, Italy · University of Granada, CITIC & DaSCI Institute, Spain

Oct 10, 2026J/K move · Enter open · S save

A Hybrid Kinematic GCN and Elastic Transformer for Efficient Indian Sign Language Recognition

Pushp Garg, Himangshu Sarma, Mrinmoy Ghorai

Human Computer Interaction Lab, IIIT SriCity, India

Sign Language Recognition Transformer

Open paper AskPDF arXiv

Sign Language Recognition (SLR) presents complex challenges due to variable signing speeds and spatial intricacies. Specifically, Indian Sign Language (ISL) requires precise modeling of its inherently bimanual nature and is bottlenecked by the scarcity of large-vocabulary benchmarks and the inability of standard models to handle irregular signing velocities. To address this, a structurally-aware hybrid framework for efficient, gloss ISL recognition is proposed. To minimize computational redundancy, an entropy-driven SVD sampler that dynamically extracts informative keyframes is used. Because this subsampling creates irregular physical time gaps, the proposed architecture employs a Continuous Dual Positional Encoding paired with a distance-aware Elastic Transformer to preserve natural signing rhythm. Spatially, a Kinematically-Conditioned Adaptive GCN explicitly models bimanual geometry using unified bone-joint features. To validate our framework, a 120-class, 9,453-video native ISL dataset is created. Augmented by Physical Node Dropout and ArcFace optimization to mitigate subject-specific memorization, our framework achieves a competitive 89.8% accuracy, establishing a strong baseline for complex sign language modeling.