Attention mechanisms and deep learning for machine vision: A survey of the state of the art

3 June 2021

Papers citing "Attention mechanisms and deep learning for machine vision: A survey of the state of the art"

8 / 8 papers shown

Title
A Comprehensive Survey on Machine Learning Driven Material Defect Detection Jun Bai Di Wu T. Shelley Peter Schubel David Twine John Russell Xuesen Zeng J. Zhang 59 6 0 12 Jun 2024
Enhancing Face Recognition with Latent Space Data Augmentation and Facial Posture Reconstruction Soroush Hashemifar Abdolreza Marefat Javad Hassannataj Joloudari H. Hassanpour CVBM 21 11 0 27 Jan 2023
Evolving Attention with Residual Convolutions Yujing Wang Yaming Yang Jiangang Bai Mingliang Zhang Jing Bai J. Yu Ce Zhang Gao Huang Yunhai Tong ViT 26 32 0 20 Feb 2021
LambdaNetworks: Modeling Long-Range Interactions Without Attention Irwan Bello 260 179 0 17 Feb 2021
Colorization Transformer Manoj Kumar Dirk Weissenborn Nal Kalchbrenner ViT 218 156 0 08 Feb 2021
Bottleneck Transformers for Visual Recognition A. Srinivas Tsung-Yi Lin Niki Parmar Jonathon Shlens Pieter Abbeel Ashish Vaswani SLR 270 979 0 27 Jan 2021
Transformers in Vision: A Survey Salman Khan Muzammal Naseer Munawar Hayat Syed Waqas Zamir F. Khan M. Shah ViT 225 2,428 0 04 Jan 2021
CrossTransformers: spatially-aware few-shot transfer Carl Doersch Ankush Gupta Andrew Zisserman ViT 201 330 0 22 Jul 2020