OCR and document
oCLIP
Weakly supervised vision-language pretraining for scene text detection and spotting.
Levelmodel
ClassOCR and document
Parametersnot in the notes
Contextnot in the notes
Released8 Mar 2022
Opennessunknown
Runs onnot in the notes
Statusactive
R&D Topics
Identity
- Developer
- Nanyang Technological University, ByteDance
- Family
- not in the notes
- Released
- 8 Mar 2022 sourcesannouncement page
- Weights published
- –
- Record checked
- 12 Oct 2026
Where this comes from
Developer and dates from the research notes. Release date is the vendor's public announcement; weights date is when open weights were published.
Architecture and Size
- Architecture
- dense transformer
- Total parameters
- – sources
- Active parameters
- –
- Checkpoint parameters
- –
- Context length
- not in the notes
- Input
- image
- Output
- text
Where this comes from
Parameter counts as the developer states them. Where the checkpoint holds a different total, both are shown (register A16).
Openness and Access
- Openness
- unknown
- Licence
- not in the notes sources
- Access routes
- open weights download
Where this comes from
The licence file governs over registry tags and aggregator labels.
Deployment
- Runs on
- not in the notes
- Footprint
- not in the notes
- Runtimes
- not in the notes
Where this comes from
Deployment tiers and runtimes as named in the notes. Footprint is the notes' figure, not a measurement by AURION.
Indonesia
- Indonesian support
- not stated
- Regional languages
- not in the notes
- Jakarta hosting
- unknown
- Languages
- not in the notes
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.
Benchmark Results
The notes record no benchmark result for this model.
Lineage
The notes record no lineage for this model.
Industry Use Cases
No industry use case links this model.
Links
ModeloCLIPNanyang Technological University, OCR and document
oCLIPNanyang Technological University, OCR and documentR&D TopicsScene and Document Text Detection and Recognition (OCR)Contrastive Image-Text Encoders (CLIP and SigLIP Lines)
Use CasesPathology Whole-Slide ImagingHealthcareUse cases of models in the same R&D topic; none is recorded for this model itself.
Who Runs Itnone recordedDeployments of these use cases; none names this model.
Organisations 2
R&D topics 2
Contrastive Image-Text Encoders (CLIP and SigLIP Lines)Image and text encoders trained together so that pictures and captions share one embeddin…produced byScene and Document Text Detection and Recognition (OCR)Finding text regions in images and reading the characters, from street signs to scanned p…produced by
Sources
- arxiv.org/abs/2203.03911 https://arxiv.org/abs/2203.03911
- github.com/open-mmlab/mmocr/tree/main/configs/backbone/o... https://github.com/open-mmlab/mmocr/tree/main/configs/backbone/oclip
- arxiv.org/html/2203.03911 https://arxiv.org/html/2203.03911
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "oCLIP", https://aurion.semai.id/models/oclip/, records of October 2026.