A comprehensive table of video sign language datasets encompassing various languages, types, and features:
| Datasets | Language | Word-Classes | Type | Videos | Signers | Availibility | Dataset link |
|---|---|---|---|---|---|---|---|
| SignBD-Word [1] | Bangla | 200 | RGB, Pose | 6000 | 16 | Public | Link to Dataset |
| Purdue RVL-SLLLASL [2] | American | 104 | RGB | 2576 | 14 | Public | Link to Dataset |
| RWTH-BOSTON-50 [3] | American | 50 | RGB | 483 | 3 | Public | Link to Dataset |
| WLASL [4] | American | 2000 | RGB | 21083 | 119 | Public | Link to Dataset |
| MS-ASL [5] | American | 1000 | RGB | 9764 | 222 | Public | Link to Dataset |
| LSA64 [6] | Argentinian | 64 | RGB, hand segmentation | 3200 | 10 | Public | Link to Dataset |
| DEVISIGN [7] | Chinese | 2000 | RGB, depth | 24000 | 8 | Public | Link to Dataset |
| Isolated SLR500 [8] | Chinese | 500 | RGB, depth, pose | 25000 | 50 | Public | Link to Dataset |
| DGS Kinect [9] | German | 40 | RGB, depth | 3000 | 15 | Public | Link to Dataset |
| GSL [10] | Greek | 20 | RGB | 840 | 6 | Public | Link to Dataset |
| INCLUDE [11] | Indian | 263 | RGB | 4287 | 7 | Public | Link to Dataset |
| PSL kinect 330 [12] | Polish | 30 | RGB, depth | 300 | - | Public | Link to Dataset |
| PSL ToF [12] | Polish | 84 | RGB, depth | 1680 | - | Public | Link to Dataset |
| AUTSL [13] | Turkish | 226 | RGB | 36302 | 43 | Public | Link to Dataset |
| NMFs-CSL [14] | Chinese | 1067 | RGB | 32010 | - | Public | Link to Dataset |
| Slovo [15] | Russian | 1000 | RGB | 20000 | 194 | Public | Link to Dataset |
| K-RSL [16] | Kazakh-Russian | 600 | RGB, pose | 28250 | 10 | Public | Link to Dataset |
References
[1] A. Sams, A. H. Akash and S. M. M. Rahman, "SignBD-Word: Video-Based Bangla Word-Level Sign Language and Pose Translation," 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT), Delhi, India, 2023, pp. 1-7, doi: 10.1109/ICCCNT56998.2023.10306914.
[2] R. Wilbur and A. Kak, "Purdue RVL-SLLL American Sign Language Database. School of Electrical and Computer Engineering Technical Report," TR-0612, Purdue University, W. Lafayette, IN 47906, Tech. Rep., 2006.
[3] M. Zahedi, P. Dreuw, D. Rybach, T. Deselaers, and H. Ney, "Continuous sign language recognition-approaches from speech recognition and available data resources," in Second Workshop on the Representation and Processing of Sign Languages: Lexicographic Matters and Didactic Scenarios, Genes, Itali, 2006, pp. 21-24.
[4] D. Li, C. Rodriguez, X. Yu, and H. Li, "Word-level deep sign language recognition from video: A new large-scale dataset and methods comparison," in Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020, pp. 1459-1469.
[5] H. R. V. Joze and O. Koller, "MS-ASL: A large-scale data set and benchmark for understanding american sign language," arXiv preprint arXiv:1812.01053, 2018.
[6] F. Ronchetti, F. Quiroga, C. A. Estrebou, L. C. Lanzarini, and A. Rosete, "LSA64: an Argentinian sign language dataset," in Proceedings of the XXII Congreso Argentino de Ciencias de la Computación, Argentina, 2016 , pp. 794-803.
[7] X. Chai, H. Wang, and X. Chen, "The devisign large vocabulary of chinese sign language database and baseline evaluations," in Technical report VIPL-TR-14-SLR-001. Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS). China: Institute of Computing Technology, 2014.
[8] J. Zhang, W. Zhou, C. Xie, J. Pu, and H. Li, "Chinese sign language recognition with adaptive HMM," in Proceedings of the IEEE International Conference on Multimedia and Expo, Seattle, WA, USA, 2016, pp. 1-6.
[9] E.-J. Ong, H. Cooper, N. Pugeault, and R. Bowden, "Sign language recognition using sequential pattern trees," in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Providence, Rhode Island, USA, 2012.
[10] E. Efthimiou and S.-E. Fotinea, "GSLC: creation and annotation of a Greek sign language corpus for HCI," in Proceedings of the International Conference on Universal Access in Human-Computer Interaction, Beijing, China, 2007, pp. 657-666.
[11] A. Sridhar, R. G. Ganesan, P. Kumar, and M. Khapra, "INCLUDE: A large scale dataset for Indian sign language recognition," in Proceedings of the International Conference on Multimedia, Seattle, United States, 2020, pp. 1366-1375.
[12] M. Oszust and M. Wysocki, "Polish sign language words recognition with kinect," in Proceedings of the 6th International Conference on Human System Interactions, Gdańsk, Sopot, Poland, 2013, pp. 219-226.
[13] O. M. Sincan and H. Y. Keles, "AUTSL: A large scale multi-modal turkish sign language dataset and baseline methods," IEEE Access, vol. 8, pp.
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