手話言語処理研究の動向 (2024年版)

This image is generated with ChatGPT-4 Omni, and edited by the author.
作成日:2024年11月18日(月) 00:00
最終更新日:2024年11月18日(月) 11:07
カテゴリ:手話言語処理
タグ:  手話言語処理 手話認識 手話翻訳 手話生成

2013年以降に発表された手話言語処理研究をリストにしてまとめました．各論文へのリンクもありますのでサーベイなどにご活用いただければ幸いです．

目次

こんにちは．高山です．
最近ふとしたキッカケで，近年発表された手話言語処理 (Sign language processing: SLP) の論文を収集する機会がありました．
折角なので本記事で整理して共有したいと思います．

公開されている論文に関しては，リンクも貼ってありますので，研究開発時のサーベイなどにご活用いただければ幸いです．

1. 収集対象と方法

今回は，下記のような方法で論文を収集しました．

  • 対象: 画像処理および機械学習関連の国際会議
    • CVPR (Computer Vision and Pattern Recognition): コンピュータビジョンやパターン認識関連のトップ会議の一つで，毎年開催されます．
      投稿数が年々増加しており，2024年は 11,532 本の論文が投稿されて 2,719 本採択されたようです (^^;)．
    • ICCV (International Conference on Computer Vision): コンピュータビジョン関連のトップ会議の一つで，隔年で開催されます．
    • ECCV (European Conference on Computer Vision): コンピュータビジョン関連のトップ会議の一つで，ICCV と交互に隔年で開催されます．
    • WACV (Winter Conference on Applications of Computer Vision): コンピュータビジョン関連の主要会議の一つで，2020年以降毎年開催されています．
    • BMVC (British Machine Vision Conference): コンピュータビジョン関連の主要会議の一つで毎年開催されています．
    • FG (International Conference on Automatic Face and Gesture Recognition): 表情や動作認識関連の専門会議です．
      開催は不定期で，他の会議より規模も小さいですが手話言語処理関連の論文が多く投稿される傾向があります．
    • NeurIPS (Neural Information Processing Systems): 機械学習と計算神経科学関連のトップ会議の一つで，毎年開催されます．
      この会議も非常に大規模な国際会議で，2023年は 12,343 本の論文が投稿されて 3,281 本採択されたようです (^^;)．
      2024年の会議はこれからですが，手話言語処理関連の投稿論文は著者らによって公開されているようです．
    • AAAI (AAAI Conference on Artificial Intelligence): 人工知能分野のトップ会議の一つで，AAAI (アメリカ人工知能学会: Association for the Advancement of Artificial Intelligence) が主催しています．
  • 収集年: 2013年 - 2024年
  • 収集方法: 各会議の論文リストから，"sign" および "finger" の単語で論文タイトルを検索し，手話言語処理関連の論文を収集

この他にも論文誌や言語関連，または福祉関連の会議を調べればもっと多量に集まると思います (例えば，ACL, EMNLP, LREC など) が，収拾がつかなくなるので今回は高山の専門分野に近い学会に対象範囲を絞りました．

2. 年度別論文数の推移

2.1 国際会議別の論文数

手話言語処理分野の動向を調査するために，まず年度別採択論文数の推移を調査してみました．
図1は，国際会議別に積み上げた年度別論文数の推移を示しています．

年度毎の手話言語処理論文数を示したグラフです．国際会議別に色分けした積み上げ棒で表現しています．画像の後に説明があります．
年度別論文数 (国際会議別)

まず一見して分かる点として，2020年から採択論文数が急増しています．
これは近年のトップ会議への投稿論文数急増も大きな要因と思いますが，Camgoz氏らの2018年の論文 [Camgoz'18] が一つのキッカケになっていると考えます．

文献 [Camgoz'18] では RNN (Recurrent neural network) Encoder-Decoder ベースの手話翻訳が提案されています．
この論文で初めて深層学習ベースの手話翻訳が提案されました．

また，この論文では同時に手話認識と手話翻訳向けのデータセットが提案されています．
数日前まで公開されていたのですが，現在は見れなくなっているようです．
一時的なリンク切れかもしれないので，後日改めて確かめて見れるようでしたらお知らせします．

深層学習を用いたアプローチが当時から現在まで続く研究トレンドと合致したこと，比較的シンプルな手法でトップ会議に通過したこと，および手法を比較できるデータセットが公開されたことなどが手話言語処理研究が2020年以降伸びてきている要因になっていると思われます．

なお，2022年は論文数が減っていますが，これは ICCV と FG が同時に未開催であったことが大きいです．

  • [Camgoz'18]: N. C. Camgoz, et al., "Neural Sign Language Translation," Proc. of the CVPR, available here, 2018.

2.2 分野別の論文数

次に，手話言語処理に関連する分野別に論文を整理しました．
図2は分野別に積み上げた年度別論文数の推移を示しています．

年度毎の手話言語処理論文数を示したグラフです．分野別に色分けした積み上げ棒で表現しています．画像の後に説明があります．
年度別論文数 (分野別)

積み上げ棒の色はそれぞれ，手話認識 (Sign language recognition)，手話翻訳 (Sign language translation)，手話生成 (Sign language production)，データセット，その他に対応しています．
主要点が複数の分野にまたがる論文は，下記の基準で一方のカテゴリに分類しています．

  • 手話認識と手話翻訳: \(\rightarrow\) 手話翻訳
  • 手話認識とデータセット: \(\rightarrow\) 手話認識
  • 手話翻訳とデータセット: \(\rightarrow\) 手話翻訳

その他には指文字認識，手話検索，手話検出，アノテーション補助，各種アプリケーションなどが含まれています．
また，手話認識と手話翻訳を混同していると思われる論文は手話認識に分類しています．

各分野とも一定の数が取り組まれていますが，最近になって手話生成の論文数が伸びているのが興味深いですね．

3. 論文一覧

最後に収集した論文の一覧を示します．
どのように並べるか少し迷いましたが，分野別に並べた方が利用しやすいと思いましたので，各項に分野別で整理してリストを示します．

3.1 手話認識

2024

  • CVPR2024
    • [Gan'24]: S. Gan, et al., "SignGraph: A Sign Sequence is Worth Graphs of Nodes," Proc of the CVPR, available here, 2024.
  • FG2024
    • [Alp'24]: A. Alp, et al., "Transfer Learning for Cross-dataset Isolated Sign Language Recognition in Under-Resourced Datasets," Proc. of the IEEE FG, available here, 2024.
    • [Ozdemir'24]: O. Ozdemiru, et al., "Hand Graph Topology Skeleton for Skeleton-based Sign Language Recognition," Proc. of the IEEE FG, available here, 2024.
  • AAAI2024
    • [Rao'24]: Q. Rao, et al., "Cross-Sentence Gloss Consistency for Continuous Sign Language Recognition," Proc. of the AAAI, available here, 2024.
    • [Lu'24]: H. Lu, et al., "TCNet: Continuous Sign Language Recognition from Trajectories and Correlated Regions," Proc. of the AAAI, available here, 2024.
  • BMVC2024
    • [Lin'24]: X. Lin, et al., "Spike-SLR: An Energy-efficient Parallel Spiking Transformer for Event-based Sign Language Recognition," Proc. of the BMVC, available here, 2024.
    • [Chen'24]: H. Chen, et al., "SignVTCL: Multi-Modal Continuous Sign Language Recognition Enhanced by Visual-Textual Contrastive Learning," Proc. of the BMVC, available here, 2024.

2023

  • ICCV2023
    • [Jiao'23]: P. Jiao, et al., "CoSign: Exploring Co-occurrence Signals in Skeleton-based Continuous Sign Language Recognition," Proc. of the ICCV, available here, 2023.
    • [Lee'23]: T. Lee, et al., "Human Part-wise 3D Motion Context Learning for Sign Language Recognition," Proc. of the ICCV, available here, 2023.
    • [Wei'23]: F. Wei, et al., "Improving Continuous Sign Language Recognition with Cross-Lingual Signs," Proc. of the ICCV, available here, 2023.
    • [Zhang'23]: H. Zhang, et al., "C\(^2\)ST: Cross-modal Contextualized Sequence Transduction for Continuous Sign Language Recognition," Proc. of the ICCV, available here, 2023.
  • CVPR2023
    • [Zuo'23]: R. Zuo, et al., "Natural Language-Assisted Sign Language Recognition," Proc. of the CVPR, available here, 2023.
    • [Guo'23]: L. Guo, et al., "Distilling Cross-Temporal Contexts for Continuous Sign Language Recognition," Proc. of the CVPR, available here, 2023.
    • [Hu'23]: L. Hu, et al., "Continuous Sign Language Recognition with Correlation Network," Proc. of the CVPR, available here, 2023.
    • [Zheng'23]: J. Zheng, et al., "CVT-SLR: Contrastive Visual-Textual Transformation for Sign Language Recognition with Variational Alignment," Proc. of the CVPR, available here, 2023.
  • FG2023
    • [Bohacek'23]: M. Bohacek, et al., "Learning from What is Already Out There: Few-shot Sign Language Recognition with Online Dictionaries," Proc. of the CVPR, available here, 2023.
  • AAAI2023
    • [Zhao'23]: W. Zhao, et al., "BEST: BERT Pre-Training for Sign Language Recognition with Coupling Tokenization," Proc. of the CVPR, available here, 2023.
    • [Hu'23]: L. Hu, et al., "Self-Emphasizing Network for Continuous Sign Language Recognition," Proc. of the CVPR, available here, 2023.

2022

  • WACV2022
    • [Kan'22]: J. Kan, et al., "Sign Language Translation with Hierarchical Spatio-TemporalGraph Neural Network," Proc. of the WACV, available here, 2022.
  • CVPR2022
    • [Zuo'22]: R. Zuo, et al., "C\(^2\)SLR: Consistency-enhanced Continuous Sign Language Recognition," Proc. of the CVPR, available here, 2022.
  • ECCV2022
    • [Hu'22]: L. Hu, et al., "Temporal Lift Pooling for Continuous Sign Language Recognition," Proc. of the CVPR, available here, 2022.
  • NeurIPS2022
    • [NC'22]: G. NC, et al., "Addressing Resource Scarcity across Sign Languages with Multilingual Pretraining and Unified-Vocabulary Datasets," Proc. of the NeurIPS, available here, 2022.
  • BMVC2022
    • [Jang'22]: Y. Jang, et al., "Signing Outside the Studio: Benchmarking Background Robustness for Continuous Sign Language Recognition," Proc. of the BMVC, available here, 2022.

2021

  • WACV2021
    • [Hosain'21]: A. A. Hosain, et al., "Hand Pose Guided 3D Pooling for Word-level Sign Language Recognition," Proc. of the WACV, available here, 2021.
  • ICCV2021
    • [Min'21]: Y. Min, et al., "Visual Alignment Constraint for Continuous Sign Language Recognition," Proc. of the ICCV, available here, 2021.
    • [Hao'21]: A. Hao, et al., "Self-Mutual Distillation Learning for Continuous Sign Language Recognition," Proc. of the ICCV, available here, 2021.
    • [Hu'21]: H. Hu, et al., "SignBERT: Pre-Training of Hand-Model-Aware Representation for Sign Language Recognition," Proc. of the ICCV, available here, 2021.
  • FG2021
    • [Sarhan'21]: N. Sarhan, et al., "Sign, Attend and Tell: Spatial Attention for Sign Language Recognition," Proc. of the IEEE FG, available here, 2021.
    • [Han'21]: Y. Han, et al., "Fusion-based Spatiotemporal Convolutions with Constant Temporal Snapshots for Sign Language Recognition," Proc. of the IEEE FG, 2021.
    • [Takayama'21]: N. Takayama, et al., "Masked Batch Normalization to Improve Tracking-Based Sign Language Recognition Using Graph Convolutional Networks," Proc. of the IEEE FG, 2021.
  • AAAI2021
    • [Hu'21]: H. Hu, et al., "Hand-Model-Aware Sign Language Recognition," Proc. of the AAAI, available here, 2021.

2020

  • CVPR2020
    • [Li'20]: D. Li, et al., "Transferring Cross-domain Knowledge for Video Sign Language Recognition," Proc. of the CVPR, available here, 2020.
  • ECCV2020
    • [Cheng'20]: K. L. Cheng, et al., "Fully Convolutional Networks for Continuous Sign Language Recognition," Proc. of the ECCV, available here, 2020.
    • [Niu'20]: Z. Niu, et al., "Stochastic Fine-grained Labeling of Multi-state Sign Glosses for Continuous Sign Language Recognition," Proc. of the ECCV, available here, 2020.
    • [Albanie'20]: S. Albanie, et al., "BSL-1K: Scaling up co-articulated sign language recognition using mouthing cues," Proc. of the ECCV, available here, 2020.
  • FG2020
    • [Hosain'20]: A. A. Hosain, et al., "FineHand: Learning Hand Shapes for American Sign Language Recognition," Proc. of the IEEE FG, available here, 2020.
  • AAAI20202
    • [Zhou'20]: H. Zhou, et al., "Spatial-Temporal Multi-Cue Network for Continuous Sign Language Recognition," Proc. of the AAAI, available here, 2020.

2019

  • CVPR2019
    • [Pu'19]: J. Pu, et al., "Iterative Alignment Network for Continuous Sign Language Recognition," Proc. of the CVPR, available here, 2019.
  • BMVC2019
    • [Bilge'19]: Y. C. Bilge, et al., "Zero-Shot Sign Language Recognition: Can Textual Data Uncover Sign Languages?," Proc. of the BMVC, available here, 2019.

2018

  • AAAI2018
    • [Huang'18]: J. Huang, et al., "Video-based Sign Language Recognition without Temporal Segmentation," Proc. of the AAAI, available here, 2018.
    • [Guo'18]: D. Guo, et al., "Hierarchical LSTM for Sign Language Translation," Proc. of the AAAI, available here, 2018.

[Guo'18] は，論文上では手話翻訳と呼んでいますが，手法や評価データセットから判断すると実態は手話認識と思われるため，手話認識のカテゴリに分類しています．

2017

  • ICCV2017
    • [Camgoz'17]: N. C. Camgoz, et al., "SubUNets: End-to-end Hand Shape and Continuous Sign Language Recognition," Proc. of the ICCV, available here, 2017.
  • CVPR2017
    • [Cui'17]: R. Cui, et al., "Recurrent Convolutional Neural Networks for Continuous Sign Language Recognition by Staged Optimization," Proc. of the CVPR, available here, 2017.

2016

  • ECCV2016
    • [Yin'16]: F. Yin, et al., "Iterative Reference Driven Metric Learning for Signer Independent Isolated Sign Language Recognition," Proc. of the ECCV, available here, 2016.
  • BMVC2016
    • [Koller'16]: O. Koller, et al., "Deep Sign: Hybrid CNN-HMM for Continuous Sign Language Recognition," Proc. of the BMVC, available here, 2016.

2015

  • FG2015
    • [Wang'15]: H. Wang, et al., "Fast Sign Language Recognition Benefited From Low Rank Approximation," Proc. of the IEEE FG, available here, 2015.
  • BMVC2015
    • [Yin'15]: F. Yin, et al., "Weakly Supervised Metric Learning towards Signer Adaptation for Sign Language Recognition," Proc. of the BMVC, available here, 2015.

2014

  • CVPR2014
    • [Ong'14]: E.-J. Ong, et al., "Sign Spotting using Hierarchical Sequential Patterns with Temporal Intervals," Proc. of the CVPR, available here, 2014.
  • ECCV2014
    • [Koller'14]: O. Koller, et al., "Read My Lips: Continuous Signer Independent Weakly Supervised Viseme Recognition," Proc. of the ECCV, available here, 2014.

3.2 手話翻訳

2024

  • CVPR2024
    • [Gong'24]: J. Gong, et al., "LLMs are Good Sign Language Translators," Proc. of the CVPR, available here, 2024.
  • ECCV2024
    • [Jiao'24]: P. Jiao, et al., "Visual Alignment Pre-training for Sign Language Translation," Proc. of the ECCV, available here, 2024.
    • [Zhang-1'24]: P. Zhang, et al., "EvSign: Sign Language Recognition and Translation with Streaming Events," Proc. of the ECCV, available here, 2024.
  • NeurIPS2024
    • [Ye'24]: J. Ye, et al., "Improving Gloss-free Sign Language Translation by Reducing Representation Density," Proc. of the NeurIPS, available here, 2024.
    • [Zhang-2'24]: B. Zhang, et al., "Scaling Sign Language Translation," Proc. of the NeurIPS, available here, 2024.
  • AAAI2024
    • [Zhao'24]: R. Zhao, et al., "Conditional Variational Autoencoder for Sign Language Translation with Cross-Modal Alignment," Proc. of the AAAI, available here, 2024.

2023

  • ICCV2023
    • [Zhou'23]: B. Zhou, et al., "Gloss-free Sign Language Translation: Improving from Visual-Language Pretraining," Proc. of the ICCV, available here, 2023.
    • [Yao'23]: H. Yao, et al., "Sign Language Translation with Iterative Prototype," Proc. of the ICCV, available here, 2023.

2022

  • CVPR2022
    • [Yin'22]: A. Yin, et al., "MLSLT: Towards Multilingual Sign Language Translation," Proc. of the CVPR, available here, 2022.
    • [Chen-1'22]: Y. Chen, et al., "A Simple Multi-Modality Transfer Learning Baseline for Sign Language Translation," Proc. of the CVPR, available here, 2022.
  • NeurIPS2022
    • [Chen-2'22]: Y. Chen, et al., "Two-Stream Network for Sign Language Recognition and Translation," Proc. of the NeurIPS, available here, 2022.

2021

  • CVPR2021
    • [Zhou'21]: H. Zhou, et al., "Improving Sign Language Translation with Monolingual Data by Sign Back-Translation," Proc. of the CVPR, available here, 2021.
  • FG2021
    • [Ananthanarayana'21]: T. Ananthanarayana, et al., "Dynamic Cross-Feature Fusion for American Sign Language Translation," Proc. of the IEEE FG, available here, 2021.

2020

  • CVPR2020
    • [Camgoz'20]: N. C. Camgoz, et al., "Sign Language Transformers: Joint End-to-end Sign Language Recognition and Translation," Proc. of the CVPR, available here, 2020.
  • FG2020
    • [Orbay'20]: A. Orbay, et al., "Neural Sign Language Translation by Learning Tokenization," Proc. of the IEEE FG, available here, 2020.
  • NeurIPS2020
    • [Li'20]: D. Li, et al., "TSPNet: Hierarchical Feature Learning via Temporal Semantic Pyramid for Sign Language Translation," Proc. of the NeurIPS, available here, 2020.

2019

  • FG2019
    • [Yuan'19]: T. Yuan, et al., "Large Scale Sign Language Interpretation," Proc. of the IEEE FG, available here, 2019.

2018

  • CVPR2018
    • [Camgoz'18]: N. C. Camgoz, et al., "Neural Sign Language Translation," Proc. of the CVPR, available here, 2018.

3.3 手話生成

2024

  • WACV2024
    • [Xie'24]: P. Xie, et al., "Sign Language Production with Latent Motion Transformer," Proc. of the WACV, available here, 2024.
  • CVPR2024
    • [Baltatzis'24]: V. Baltatzis, et al., "Neural Sign Actors: A diffusion model for 3D sign language production from text," Proc. of the CVPR, available here, 2024.
  • ECCV2024
    • [Shi'24]: T. Shi, et al., "Pose-Guided Fine-Grained Sign Language Video Generation," Proc. of the ECCV, available here, 2024.
    • [Qi'24]: F. Qi, et al., "SignGen: End-to-End Sign Language Video Generation with Latent Diffusion," Proc. of the ECCV, available here, 2024.
    • [Zuo'24]: R. Zuo, et al., "A Simple Baseline for Spoken Language to Sign Language Translation with 3D Avatars," Proc. of the ECCV, available here, 2024.
  • FG2024
    • [Hwang'24]: E. J. Hwang, et al., "A Gloss-free Sign Language Production with Discrete Representation," Proc. of the IEEE FG, available here, 2024.
    • [Walsh'24]: H. Walsh, et al., "A Data-Driven Representation for Sign Language Production," Proc. of the IEEE FG, available here, 2024.
    • [Barros'24]: J. M. D. Barros, et al., "SynthSL: Expressive Humans for Sign Language Image Synthesis," Proc. of the IEEE FG, available here, 2024.
    • [Lakhal'24]: M. L. Lakhal, et al., "Diversity-Aware Sign Language Production through a Pose Encoding Variational Autoencoder," Proc. of the IEEE FG, available here, 2024.
    • [Dong'24]: L. Dong, et al., "SignAvatar: Sign Language 3D Motion Reconstruction and Generation," Proc. of the IEEE FG, available here, 2024.
  • AAAI2024
    • [Xie'24]: P. Xie, et al., "G2P-DDM: Generating Sign Pose Sequence from Gloss Sequence with Discrete Diffusion Model," Proc. of the AAAI, available here, 2024.
  • BMVC2024
    • [Walsh'24]: H. Walsh, et al., "Sign Stitching: A Novel Approach to Sign Language Production," Proc. of the BMVC, available here, 2024.

2023

  • CVPR2023
    • [Arkushin'23]: R. S. Arkushin, et al., "Ham2Pose: Animating Sign Language Notation into Pose Sequences," Proc. of the CVPR, available here, 2023.
  • FG2023
    • [Gibet'23]: S. Gibet, et al., "Signing Avatars - Multimodal Challenges for Text-to-sign Generation," Proc. of the IEEE FG, 2023.
    • [Ananthanarayana'23]: T. Ananthanarayana, et al., "SignNet: Single Channel Sign Generation using Metric Embedded Learning," Proc. of the IEEE FG, available here, 2023.

2022

  • CVPR2022
    • [Saunders'22]: B. Saunders, et al., "Signing at Scale: Learning to Co-Articulate Signs for Large-Scale Photo-Realistic Sign Language Production," Proc. of the CVPR, available here, 2022.

2021

  • ICCV2021
    • [Saunders'21]: B. Saunders, et al., "Mixed SIGNals: Sign Language Production via a Mixture of Motion Primitives," Proc. of the CVPR, available here, 2021.
  • BMVC2021
    • [Hwang'21]: E. J. Hwang, et al., "Non-Autoregressive Sign Language Production with Gaussian Space," Proc. of the BMVC, available here, 2021.

2020

  • WACV2020
    • [Zelinka'20]: J. Zelinka, et al., "Neural Sign Language Synthesis: Words Are Our Glosses," Proc. of the WACV, available here, 2020.
  • ECCV2020
    • [Saunders-1'20]: B. Saunders, et al., "Progressive Transformers for End-to-End Sign Language Production," Proc. of the ECCV, available here, 2020.
  • BMVC2020
    • [Saunders-2'20]: B. Saunders, et al., "Adversarial Training for Multi-Channel Sign Language Production," Proc. of the BMVC, available here, 2020.

2018

  • BMVC2018
    • [Stoll'18]: S. Stoll, et al., "Sign Language Production using Neural Machine Translation and Generative Adversarial Networks," Proc. of the BMVC, available here, 2018.

3.4 データセット

2024

  • ECCV2024
    • [Yu'24]: Z. Yu, et al., "SignAvatars: A Large-scale 3D Sign Language Holistic Motion Dataset and Benchmark," Proc. of the ECCV, available here, 2024.
  • FG2024
    • [Zeeon'24]: I. E. M. Zeeon, et al., "BTVSL: A Novel Sentence-Level Annotated Dataset for Bangla Sign Language Translation," Proc. of the IEEE FG, available here, 2024.
  • NeurIPS2024
    • [Shen'24]: X. Shen, et al., "MM-WLAuslan: Multi-View Multi-Modal Word-Level Australian Sign Language Recognition Dataset," Proc. of the IEEE FG, available here, 2024.

2023

  • FG2023
    • [Luqman'23]: H. Luqman, et al., "ArabSign: A Multi-modality Dataset and Benchmark for Continuous Arabic Sign Language Recognition," Proc. of the IEEE FG, available here, 2023.
  • NeurIPS2023
    • [Shen'23]: X. Shen, et al., "Auslan-Daily: Australian Sign Language Translation for Daily Communication and News," Proc. of the NeurIPS, available here, 2023.
    • [Desai'23]: A. Desai, et al., "ASL Citizen: A Community-Sourced Dataset for Advancing Isolated Sign Language Recognition," Proc. of the NeurIPS, available here, 2023.
    • [Uthus'23]: D. Uthus, et al., "YouTube-ASL: A Large-Scale, Open-Domain American Sign Language-English Parallel Corpus," Proc. of the NeurIPS, available here, 2023.
    • [Starner'23]: T. Starner, et al., "PopSign ASL v1.0: An Isolated American Sign Language Dataset Collected via Smartphones," Proc. of the NeurIPS, available here, 2023.

2021

  • FG2021
    • [Ham'21]: S. Ham, et al., "KSL-Guide: A Large-scale Korean Sign Language Dataset Including Interrogative Sentences for Guiding the Deaf and Hard-of-Hearing," Proc. of the IEEE FG, 2021.
    • [Camgoz'21]: N. C. Camgoz, et al., "Content4All Open Research Sign Language Translation Datasets," Proc. of the IEEE FG, available here, 2021.
  • CVPR2021
    • [Duarte'21]: A. Duarte, et al., "How2Sign: A Large-scale Multimodal Dataset for Continuous American Sign Language," Proc. of the CVPR, available here, 2021.

2020

  • WACV2020
    • [Li'20]: D. Li, et al., "Word-level Deep Sign Language Recognition from Video: A New Large-scale Dataset and Methods Comparison," Proc. of the WACV, available here, 2020.
  • FG2020
    • [Silva'20]: E. P. da Silva, et al., "SILFA: Sign Language Facial Action Database for the Development of Assistive Technologies for the Deaf," Proc. of the IEEE FG, 2020.
    • [Vasudevan'20]: A. Vasudevan, et al., "Introduction and Analysis of an Event-Based Sign Language Dataset," Proc. of the IEEE FG, available here, 2020.
    • [Kosmopoulos'20]: D. Kosmopoulos, et al., "Towards a visual Sign Language dataset for home care services," Proc. of the IEEE FG, available here, 2020.

2019

  • BMVC2019
    • [Joze'19]: H. R. V. Joze, et al., "MS-ASL: A Large-Scale Data Set and Benchmark for Understanding American Sign Language," Proc. of the BMVC, available here, 2019.

3.5 その他

2024

  • ECCV2024
    • [Wu'24]: X. Wu, et al., "Uncertainty-aware sign language video retrieval with probability distribution modeling," Proc. of the ECCV, available here, 2024.
  • FG2024
    • [Xu'24]: F. Xu, et al., "A Comparative Study of Video-based Human Representations for American Sign Language Alphabet Generation," Proc. of the IEEE FG, available here, 2024.
    • [Novopoltsev'24]: M. Novopoltsev, et al., "Russian sign language learning simulator - FG 2024 Submission," Proc. of the IEEE FG, available here, 2024.
    • [Tasyurek'24]: S. M. Tasyurek, et al., "Towards Better Communication: Refining Hand Pose Estimation in Low-Resolution Sign Language Videos," Proc. of the IEEE FG, available here, 2024.
  • AAAI2024:
    • [Pallickara'24]: D. Pallickara, et al., "A Wireframe-Based Approach for Classifying and Acquiring Proficiency in the American Sign Language," Proc. of the AAAI (Student Abstract), available here, 2024.
    • [Medronha'24]: A. Medronha, et al., "LERMO: A Novel Web Game for AI-Enhanced Sign Language Recognition," Proc. of the AAAI (Student Abstract), available here, 2024.

2023

  • CVPR2023
    • [Cheng'23]: Y. Cheng, et al., "CiCo: Domain-Aware Sign Language Retrieval via Cross-Lingual Contrastive Learning," Proc. of the CVPR, available here, 2023.

2022

  • CVPR2022
    • [Duarte'22]: A. Duarte, et al., "Sign Language Video Retrieval with Free-Form Textual Queries," Proc. of the CVPR, available here, 2022.
  • ECCV2022
    • [Momeni'22]: L. Momeni, et al., "Automatic dense annotation of large-vocabulary sign language videos," Proc. of the ECCV, available here, 2022.
  • BMVC2022
    • [Prajwal'22]: K. R. Prajwal, et al., "Weakly-supervised Fingerspelling Recognition in British Sign Language Videos," Proc. of the BMVC, available here, 2022.

2021

  • ICCV2021
    • [Bull'21]: H. Bull, et al., "Aligning Subtitles in Sign Language Videos," Proc. of the ICCV, available here, 2021.
  • CVPR2021
    • [Varol'21]: G. Varol, et al., "Read and Attend: Temporal Localisation in Sign Language Videos," Proc. of the CVPR, available here, 2021.
    • [Shi'21]: B. Shi, et al., "Fingerspelling Detection in American Sign Language," Proc. of the CVPR, available here, 2021.
  • FG2021
    • [Jiang'21]: T. Jiang, et al., "Looking for the Signs: Identifying Isolated Sign Instances in Continuous Video Footage," Proc. of the IEEE FG, available here, 2021.
    • [Saunders'21]: B. Saunders, et al., "AnonySIGN: Novel Human Appearance Synthesis for Sign Language Video Anonymisation," Proc. of the IEEE FG, available here, 2021.
  • AAAI2021
    • [Ananthanarayana'21]: T. Ananthanarayana, "A Computational Approach to Sign Language Understanding," Proc. of the AAAI, available here, 2021.
  • BMVC2021
    • [Sartinas'21]: E. G. Sartinas, "A 2-D Wrist Motion Based Sign Language Video Summarization," Proc. of the BMVC, available here, 2021.

2020

  • FG2020
    • [Schioppo'20]: J. Schioppo, et al., "Sign Language Recognition in Virtual Reality," Proc. of the IEEE FG, available here, 2020.
  • AAAI2020
    • [Du'20]: Y. Du, "American Sign Language Recognition Using an FMCW Wireless Sensor," Proc. of the AAAI (Student Abstract), available here, 2020.

2019

  • ICCV2019
    • [Shi'19]: B. Shi, "Fingerspelling recognition in the wild with iterative visual attention," Proc. of the ICCV, available here, 2019.

2015

  • FG2015
    • [Antonakos'15]: E. Antonakos, et al., "A Survey on Mouth Modeling and Analysis for Sign Language Recognition," Proc. of the IEEE FG, available here, 2015.
    • [Zafrulla'15]: Z. Zafrulla, et al., "Hand detection in American Sign Language depth data using domain-driven random forest regression," Proc. of the IEEE FG, 2015.

2013

  • ICCV2013
    • [Kim'13]: T. Kim, et al., "Fingerspelling recognition with semi-Markov conditional random fields," Proc. of the ICCV, available here, 2013.
  • FG2013
    • [Liu'13]: J. Liu, et al., "Recognizing Eyebrow and Periodic Head Gestures Using CRFs for Non-Manual Grammatical Marker Detection in ASL," Proc. of the FG, available here, 2013.
    • [Koller'13]: O. Koller, et al., "May the Force be with you: Force-Aligned SignWriting for Automatic Subunit Annotation of Corpora," Proc. of the FG, available here, 2013.
  • BMVC2013
    • [Charles'13]: J. Charles, et al., "Domain Adaptation for Upper Body Pose Tracking in Signed TV Broadcasts," Proc. of the BMVC, available here, 2013.
    • [Pfister'13]: T. Pfister, et al., "Large-scale Learning of Sign Language by Watching TV (Using Co-occurrences)," Proc. of the BMVC, available here, 2013.

今回は手話言語処理関連の論文を紹介しましたが，如何でしたでしょうか?
他の分野に比べればまだ追える範囲ですが，それでも結構多いですね (^^;)．

途中で挫折すると思ったので (^^;)，論文の要約などはしませんでしたが，簡単な紹介などは折を見て記事にできたらいいなと思っています．
今回紹介した話が，これから手話言語処理を勉強してみようとお考えの方に何か参考になれば幸いです．

実践手話認識 - モデル開発編6: Temporal CNNで孤立手話単語認識モデルを改良

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