Channel Attention Multi-Branch Network for Fine-Grained Image Recognition

Binzhou Wang; Zhiyong Xiao

doi:10.3788/LOP202158.2210008

[1] Zhao Z Y, Cheng Y L, Shi X S et al. Terrain classification of LiDAR point cloud based on multi-scale features and PointNet[J]. Laser & Optoelectronics Progress, 56, 052804(2019).

[2] Wei X S, Xie C W, Wu J X et al. Mask-CNN: localizing parts and selecting descriptors for fine-grained bird species categorization[J]. Pattern Recognition, 76, 704-714(2018).

[3] Li S Y, Liu Y H, Zhang R F. Fine-grained image classification based on multi-scale feature fusion[J]. Laser & Optoelectronics Progress, 57, 121002(2020).

[4] Lin X N, Qin F W, Peng Y et al. Fine-grained pornographic image recognition with multiple feature fusion transfer learning[J]. International Journal of Machine Learning and Cybernetics, 12, 73-86(2021).

[5] Zhang H, Xu T, Elhoseiny M et al. SPDA-CNN: unifying semantic part detection and abstraction for fine-grained recognition[C]. //2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA, 1143-1152(2016).

[6] Fu J L, Zheng H L, Mei T. Look closer to see better: recurrent attention convolutional neural network for fine-grained image recognition[C]. //2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA, 4476-4484(2017).

[7] Zhang F, Li M, Zhai G S et al. Multi-branch and multi-scale attention learning for fine-grained visual categorization[EB/OL]. (2020-07-21)[2021-01-03]. https:// arxiv.org/abs/2003.09150

[8] Yang Z, Luo T G, Wang D et al. Learning to navigate for fine-grained classification[M]. //Ferrari V, Hebert M, Sminchisescu C, et al. Computer vision-ECCV 2018. Lecture notes in computer science, 11218, 438-454(2018).

[9] Zoph B, Vasudevan V, Shlens J et al. Learning transferable architectures for scalable image recognition[C]. //2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA., 8697-8710(2018).

[10] Lin T Y, RoyChowdhury A, Maji S. Bilinear CNN models for fine-grained visual recognition[C]. //2015 IEEE International Conference on Computer Vision (ICCV), December 7-13, 2015, Santiago, Chile., 1449-1457(2015).

[11] Li Q N, Sun H X, Sun K J. Fine-grained classification of sleeper shoulder crack images based on improved B-CNN[J]. Laser & Optoelectronics Progress, 57, 141013(2020).

[12] Liu K, Wang D, Rong M X. X-ray image classification algorithm based on semi-supervised generative adversarial networks[J]. Acta Optica Sinica, 39, 0810003(2019).

[13] Xu Z J, Wang D. Multi-pose face recognition with two-cycle generative adversarial network[J]. Acta Optica Sinica, 40, 1910002(2020).

[14] Sermanet P, Eigen D, Zhang X et al. Overfeat:integrated recognition, localization and detection using convolutional networks[EB/OL]. (2014-02-24)[2021-01-03]. https://arxiv.org/abs/1312.6229

[15] Wang Q L, Wu B G, Zhu P F et al. ECA-Net: efficient channel attention for deep convolutional neural networks[C]. //2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 13-19, 2020, Seattle, WA, USA, 11531-11539(2020).

[16] Zheng Z H, Wang P, Liu W et al. Distance-IoU loss: faster and better learning for bounding box regression[J]. Proceedings of the AAAI Conference on Artificial Intelligence, 34, 12993-13000(2020).

[17] Woo S, Park J, Lee J Y et al. CBAM: convolutional block attention module[M]. //Ferrari V, Hebert M, Sminchisescu C, et al. Computer vision-ECCV 2018. Lecture notes in computer science, 11211, 3-19(2018).

[18] Hu J, Shen L, Albanie S et al. Squeeze-and-excitation networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42, 2011-2023(2020).

[19] Cao J M, Li Y Y, Sun M C et al. DO-Conv:depthwise over-parameterized convolutional layer[EB/OL]. (2020-06-22)[2021-01-03]. https://arxiv.org/abs/2006.12030

[20] Lam M, Mahasseni B, Todorovic S. Fine-grained recognition as HSnet search for informative image parts[C]. //2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA., 6497-6506(2017).

[21] Han K, Guo J Y, Zhang C et al. Attribute-aware attention model for fine-grained representation learning[C]. //Proceedings of the 26th ACM International Conference on Multimedia,October 22-26, 2018, Seoul Republic of Korea, 2040-2048(2018).

[22] Martinel N, Foresti G L, Micheloni C. Wide-slice residual networks for food recognition[C]. //2018 IEEE Winter Conference on Applications of Computer Vision (WACV),March 12-15, 2018, Lake Tahoe, NV, USA., 567-576(2018).

[23] Zheng J N, Zou L, Wang Z J. Mid-level deep food part mining for food image recognition[J]. IET Computer Vision, 12, 298-304(2018).