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Cited by 1,205

The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.

Attention Augmented Convolutional Networks

Open access
Bello, Irwan, Zoph, Barret, Le, Quoc, Vaswani, Ashish, Shlens, Jonathon·2019·2019 IEEE/CVF International Conference on Computer Vision (ICCV)
DOI 10.1109/iccv.2019.00338
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Abstract

Convolutional networks have enjoyed much success in many computer vision applications. The convolution operation however has a significant weakness in that it only operates on a local neighbourhood, thus missing global information. Self-attention, on the other hand, has emerged as a recent advance to capture long range interactions, but has mostly been applied to sequence modeling and generative modeling tasks. In this paper, we propose to augment convolutional networks with self-attention by concatenating convolutional feature maps with a set of feature maps produced via a novel relative self-attention mechanism. In particular, we extend previous work on relative self-attention over sequences to images and discuss a memory efficient implementation. Unlike Squeeze-and-Excitation, which performs attention over the channels and ignores spatial information, our self-attention mechanism attends jointly to both features and spatial locations while preserving translation equivariance. We find that Attention Augmentation leads to consistent improvements in image classification on ImageNet and object detection on COCO across many different models and scales, including ResNets and a state-of-the art mobile constrained network, while keeping the number of parameters similar. In particular, our method achieves a 1.3% top-1 accuracy improvement on ImageNet classification over a ResNet50 baseline and outperforms other attention mechanisms for images such as Squeeze-and-Excitation. It also achieves an improvement of 1.4 AP in COCO Object Detection on top of a RetinaNet baseline.

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Cites

Show all 26 references

Research works printed but not linked: 32

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Metadata

Authors
Bello, I., Zoph, B., Le, Q., Vaswani, A., & Shlens, J.
Venue
2019 IEEE/CVF International Conference on Computer Vision (ICCV)
Publisher
IEEE
Published
2019-10
Pages
3285-3294
DOI
10.1109/iccv.2019.00338
OpenAlex
W2937843571
Cited by
1,205
References
26
FWCI
53.64
Type
conference paper
Language
en
Open access
green
Licence

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CoChat. (2026). Citation check: Attention Augmented Convolutional Networks. https://app.cochat.ai/papers/10.1109/iccv.2019.00338
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Bello, I., Zoph, B., Le, Q., Vaswani, A., & Shlens, J. (2019). Attention Augmented Convolutional Networks. 2019 IEEE/CVF International Conference on Computer Vision (ICCV). https://doi.org/10.1109/iccv.2019.00338

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