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| Hauptseite > Publikationsdatenbank > LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs > print |
| Hauptseite > Publikationsdatenbank > LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs > print |
| 001 | 905696 | ||
| 005 | 20220131120340.0 | ||
| 024 | 7 | _ | |a 2128/30478 |2 Handle |
| 037 | _ | _ | |a FZJ-2022-00923 |
| 100 | 1 | _ | |a Schuhmann, Christoph |0 P:(DE-HGF)0 |b 0 |
| 111 | 2 | _ | |a NeurIPS Workshop Datacentric AI |g DCAI2021 |c online |d 2021-12-14 - 2021-12-14 |w online |
| 245 | _ | _ | |a LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs |
| 260 | _ | _ | |c 2021 |
| 300 | _ | _ | |a 5 p. |
| 336 | 7 | _ | |a CONFERENCE_PAPER |2 ORCID |
| 336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
| 336 | 7 | _ | |a INPROCEEDINGS |2 BibTeX |
| 336 | 7 | _ | |a conferenceObject |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Conference Paper |2 DataCite |
| 336 | 7 | _ | |a Contribution to a conference proceedings |b contrib |m contrib |0 PUB:(DE-HGF)8 |s 1642841436_7299 |2 PUB:(DE-HGF) |
| 520 | _ | _ | |a Multi-modal language-vision models trained on hundreds of millions of image-textpairs (e.g. CLIP, DALL-E) gained a recent surge, showing remarkable capability toperform zero- or few-shot learning and transfer even in absence of per-sample labelson target image data. Despite this trend, to date there has been no publicly availabledatasets of sufficient scale for training such models from scratch. To address thisissue, in a community effort we build and release for public LAION-400M, adataset with CLIP-filtered 400 million image-text pairs, their CLIP embeddingsand kNN indices that allow efficient similarity search |
| 536 | _ | _ | |a 5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511) |0 G:(DE-HGF)POF4-5112 |c POF4-511 |f POF IV |x 0 |
| 588 | _ | _ | |a Dataset connected to DataCite |
| 700 | 1 | _ | |a Vencu, Richard |0 P:(DE-HGF)0 |b 1 |
| 700 | 1 | _ | |a Beaumont, Romain |0 P:(DE-HGF)0 |b 2 |
| 700 | 1 | _ | |a Kaczmarczyk, Robert |0 P:(DE-HGF)0 |b 3 |
| 700 | 1 | _ | |a Mullis, Clayton |0 P:(DE-HGF)0 |b 4 |
| 700 | 1 | _ | |a Katta, Aarush |0 P:(DE-HGF)0 |b 5 |
| 700 | 1 | _ | |a Coombes, Theo |0 P:(DE-HGF)0 |b 6 |
| 700 | 1 | _ | |a Jitsev, Jenia |0 P:(DE-Juel1)158080 |b 7 |
| 700 | 1 | _ | |a Komatsuzaki, Aran |0 P:(DE-HGF)0 |b 8 |
| 856 | 4 | _ | |u https://arxiv.org/abs/2111.02114 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/905696/files/159_CameraReady_Workshop_Submission_LAION_400M__Public_Dataset_with_CLIP_Filtered_400M_Image_Text_Pairs-1.pdf |y OpenAccess |
| 909 | C | O | |o oai:juser.fz-juelich.de:905696 |p openaire |p open_access |p VDB |p driver |p dnbdelivery |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 7 |6 P:(DE-Juel1)158080 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Engineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action |1 G:(DE-HGF)POF4-510 |0 G:(DE-HGF)POF4-511 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-500 |4 G:(DE-HGF)POF |v Enabling Computational- & Data-Intensive Science and Engineering |9 G:(DE-HGF)POF4-5112 |x 0 |
| 914 | 1 | _ | |y 2021 |
| 915 | _ | _ | |a OpenAccess |0 StatID:(DE-HGF)0510 |2 StatID |
| 920 | 1 | _ | |0 I:(DE-Juel1)JSC-20090406 |k JSC |l Jülich Supercomputing Center |x 0 |
| 980 | _ | _ | |a contrib |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a UNRESTRICTED |
| 980 | _ | _ | |a I:(DE-Juel1)JSC-20090406 |
| 980 | 1 | _ | |a FullTexts |
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