e-ViL: A Dataset and Benchmark for Natural Language Explanations in 
Vision-Language Tasks

Kayser, Maxime; Camburu, Oana-Maria; Salewski, Leonard; Emde, Cornelius; Do, Virginie; Akata, Zeynep; Lukasiewicz, Thomas

doi:10.1109/ICCV48922.2021.00128

Item

ITEM ACTIONSEXPORT

Add to Basket

Local TagsRelease HistoryDetailsSummary

Released

Conference Paper

e-ViL: A Dataset and Benchmark for Natural Language Explanations in Vision-Language Tasks

MPS-Authors

/persons/resource/persons127761

Akata, Zeynep
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society;

External Resource

No external resources are shared

Fulltext (restricted access)

There are currently no full texts shared for your IP range.

Fulltext (public)

Kayser_E-ViL_A_Dataset_and_Benchmark_for_Natural_Language_Explanations_in_ICCV_2021_paper.pdf
(Preprint), 702KB

Supplementary Material (public)

There is no public supplementary material available

Citation

Kayser, M., Camburu, O.-M., Salewski, L., Emde, C., Do, V., Akata, Z., et al. (2021). e-ViL: A Dataset and Benchmark for Natural Language Explanations in Vision-Language Tasks. In ICCV 2021 (pp. 1224-1234). Piscataway, NJ: IEEE. doi:10.1109/ICCV48922.2021.00128.

Cite as: https://hdl.handle.net/21.11116/0000-0009-89CE-5

Abstract

There is no abstract available