Browse State-of-the-Art › Sign Language Recognition
Sign Language Recognition
95 papers with code · 19 benchmarks · 30 datasets archive 2025-07-28
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.
( Image credit: Word-level Deep Sign Language Recognition from Video: A New Large-scale Dataset and Methods Comparison )
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
19 leaderboard tables shown for this task, 19 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted. 10 shown of 19 until expanded.
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
30 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Most implemented papers archive 2025-07-28
30 shown of 95 papers with code (297 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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3 May 2017 8 repositories listedLow-cost consumer depth cameras and deep learning have enabled reasonable 3D hand pose estimation from single depth images.
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17 Jun 2020 7 repositories listedWe present BlazePose, a lightweight convolutional neural network architecture for human pose estimation that is tailored for real-time inference on mobile devices.
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8 Mar 2022 4 repositories listed Syntology ran 5 of 10 samples · 5 unverified · 9 pointer-only (licence)Concretely, we pretrain the sign-to-gloss visual network on the general domain of human actions and the within-domain of a sign-to-gloss dataset, and pretrain the gloss-to-text translation network on the general domain…
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6 Mar 2023 3 repositories listed Syntology ran 5 of 6 samples · 1 unverified · 6 pointer-only (licence)Visualizations demonstrate the effects of CorrNet on emphasizing human body trajectories across adjacent frames.
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16 Mar 2021 3 repositories listedSign language is commonly used by deaf or speech impaired people to communicate but requires significant effort to master.
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24 Oct 2019 3 repositories listed Syntology ran 0 of 7 samples · 7 unverifiedBased 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.
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11 Feb 2023 2 repositories listedWe use insights from research on American Sign Language (ASL) phonology to train models for isolated sign language recognition (ISLR), a step towards automatic sign language understanding.
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30 Nov 2022 2 repositories listed Syntology ran 1 of 1 samples · 0 unverifiedTo relieve this problem, we propose a self-emphasizing network (SEN) to emphasize informative spatial regions in a self-motivated way, with few extra computations and without additional expensive supervision.
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12 Oct 2021 2 repositories listedCurrent Sign Language Recognition (SLR) methods usually extract features via deep neural networks and suffer overfitting due to limited and noisy data.
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6 Apr 2021 2 repositories listed Syntology ran 4 of 5 samples · 1 unverified · 3 pointer-only (licence)Specifically, the proposed VAC comprises two auxiliary losses: one focuses on visual features only, and the other enforces prediction alignment between the feature extractor and the alignment module.
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12 Jan 2021 2 repositories listedFor that reason, we apply attention to synchronize and help capture entangled dependencies between the different sign language components.
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1 Jan 2021 2 repositories listedThe availability of a comprehensive benchmarking database for ArSL is one of the challenges of the automatic recognition of Arabic Sign language.
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12 Oct 2020 2 repositories listed Syntology ran 6 of 6 samples · 0 unverified · 3 pointer-only (licence)Sign language translation (SLT) aims to interpret sign video sequences into text-based natural language sentences.
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30 Mar 2020 2 repositories listed Syntology ran 1 of 7 samples · 6 unverifiedWe report state-of-the-art sign language recognition and translation results achieved by our Sign Language Transformers.
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28 Aug 2019 2 repositories listedIn 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.
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1 Oct 2017 2 repositories listedWe propose a novel deep learning approach to solve simultaneous alignment and recognition problems (referred to as "Sequence-to-sequence" learning).
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26 Jun 2025 1 repository listedSpecifically, we construct an HST for textual information representation, aligning visual and textual modalities step-by-step and benefiting from the tree structure to reduce computational complexity.
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18 Jun 2025 1 repository listedThis study offers a reliable and effective approach for sign language recognition, with strong potential for enhancing accessibility tools for the deaf and hard of hearing.
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11 Jun 2025 1 repository listedSign Language Recognition (SLR) plays a crucial role in bridging the communication gap between the hearing-impaired community and society.
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20 May 2025 1 repository listedSign Language Recognition (SLR) systems primarily focus on manual gestures, but non-manual features such as mouth movements, specifically mouthing, provide valuable linguistic information.
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15 May 2025 1 repository listedMoreover, the models demonstrate high performance on the first open dataset for Russian fingerspelling, Znaki, presented in this paper.
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2 Apr 2025 1 repository listedWe introduce two variants, SLA-Adapter and SLA-LoRA, which integrate PEFT modules into the CLIP visual encoder, enabling fine-tuning with minimal trainable parameters.
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26 Mar 2025 1 repository listedFor LSA64, we achieve a top-1 accuracy of 99.
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7 Feb 2025 1 repository listedTo address these issues, we present the Swin multiscale temporal perception (Swin-MSTP) framework, in which the Swin Transformer is utilized as the spatial feature extractor, capable of capturing fine spatial details…
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4 Feb 2025 1 repository listedIn this paper, we present our solution to the Cross-View Isolated Sign Language Recognition (CV-ISLR) challenge held at WWW 2025.
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25 Jan 2025 1 repository listed Syntology ran 14 of 15 samples · 1 unverified · 15 pointer-only (licence)Sign language pre-training has gained increasing attention for its ability to enhance performance across various sign language understanding (SLU) tasks.
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4 Dec 2024 1 repository listedThis diverse training scheme establishes superior accuracy benchmarks: achieving an impressive 100% on INCLUDE-50, 94.
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19 Nov 2024 1 repository listedWe present a comprehensive Azerbaijani Sign Language Dataset (AzSLD) collected from diverse sign language users and linguistic parameters to facilitate advancements in sign recognition and translation systems and…
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11 Oct 2024 1 repository listedThis paper investigates the recognition of the Russian fingerspelling alphabet, also known as the Russian Sign Language (RSL) dactyl.
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18 Sep 2024 1 repository listedThe current bottleneck in continuous sign language recognition (CSLR) research lies in the fact that most publicly available datasets are limited to laboratory environments or television program recordings, resulting in…
Syntology lines on 8 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
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