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The SignEval 2025 Challenge at the ICCV Multimodal Sign Language Recognition Workshop: Results and Discussion

Luqman, Hamzah
; 
Mineo, Raffaele
; 
Aljubran, Murtadha
; 
Hasanaath, Ahmed Abul
; 
Sorrenti, Amelia
; 
Alyami, Sarah
; 
Al-Azani, Sadam
; 
Alowaifeer, Maad
; 
Moon, JiHwan
; 
Javorek, Vaclav
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Author
Luqman, Hamzah
Mineo, Raffaele
Aljubran, Murtadha
Hasanaath, Ahmed Abul
Sorrenti, Amelia
Alyami, Sarah
Al-Azani, Sadam
Alowaifeer, Maad
Moon, JiHwan
Javorek, Vaclav
Zelezny, Tomas
Hruz, Marek
Caligiore, Gaia
Giancola, Silvio
Polikovsky, Senya
Alfarraj, Motaz
Fontana, Sabina
Mahmud, Mufti
Khan, Muhammad Haris
Islam, Kamrul
Gurbuz, Sevgi
Ragonese, Egidio
Bellitto, Giovanni
Salanitri, Federica Proietto
Spampinato, Concetto
Palazzo, Simone
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Department
Computer Vision
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Conference proceeding
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Abstract
This paper summarizes the results of the first multimodal sign language recognition challenge, SignEval 2025, organized at ICCV 2025. The challenge featured two tracks: (i) Continuous sign language recognition (CSLR) task based on the newly curated Isharah dataset, a Saudi Sign Language dataset, and (ii) Isolated sign language recognition (ISLR) task using the MultiMeDaLIS dataset, a multimodal Italian Sign Language corpus tailored for doctor-patient communication. Two tasks are defined within the CSLR track: Signer-Independent and Unseen-Sentences. The Signer-Independent task tests the model's ability to generalize across signers, a critical property for scalable real-world CSLR systems. The UnseenSentences task evaluates the model's capability to recognize novel sentence compositions by leveraging learned grammar and semantics. The ISLR track utilized MultiMeDaLIS, a multi-modal dataset. The participants of this track were challenged to classify isolated signs using only radar and RGB modalities. The challenge utilized two leaderboards to showcase methods, with participants setting new benchmarks and achieving state-of-the-art results on both tracks. More information on the challenges, tasks, leaderboard, baselines and development kits are available on https://multimodal-signlanguage-recognition.github.io/ICCV-2025/.
Citation
H. Luqman, R. Mineo, M. Aljubran, A.A. Hasanaath, A. Sorrenti, S. Alyami , et al., "The SignEval 2025 Challenge at the ICCV Multimodal Sign Language Recognition Workshop: Results and Discussion," 2025, pp. 5086-5095.
Source
2025 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)
Conference
2025 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)
Keywords
46 Information and Computing Sciences, 4608 Human-Centred Computing, 47 Language, Communication and Culture, 4704 Linguistics
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Source
2025 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)
Publisher
IEEE
DOI
10.1109/iccvw69036.2025.00529
Additional links
https://ieeexplore.ieee.org/document/11375246
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