Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers-Reference-Cited by-同舟云学术

Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers

Published:2021-10 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE/CVF International Conference on Computer Vision (ICCV)
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Author:

Chefer Hila¹,Gur Shir¹,Wolf Lior¹

Affiliation:

1. Tel Aviv University,The School of Computer Science

Funder

European Research Council

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9709627/9709628/09710570.pdf?arnumber=9710570

Reference50 articles.

1. Training data-efficient image transformers & distillation through attention;touvron,2020

2. LXMERT: Learning Cross-Modality Encoder Representations from Transformers

3. Learning important features through propagating activation differences;shrikumar;Proceedings of the 34th International Conference on Machine Learning-Volume 70,2017

4. Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization

5. ImageNet Large Scale Visual Recognition Challenge

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