Journal of Applied Optics, Volume. 46, Issue 2, 327(2025)
PSMNet algorithm based on dual three-pooling attention mechanism
[1] A KAKADE, M DESHPANDE, S SARDESHPANDE et al. 3D modelling using sequential and convolutional generative adversarial networks, 1-4(2021).
[2] K MIN, S HAN, D LEE et al. SAE Level 3 Autonomous driving technology of the ETRI, 464-466(2019).
[3] J L YANG, P R REN, D Q ZHANG et al. Neural aggregation network for video face recognition, 5216-5225(2017).
[4] N ZENATI, N ZERHOUNI. Dense stereo matching with application to augmented reality, 1503-1506(2007).
[5] H HIRSCHMULLER. Accurate and efficient stereo processing by semi-global matching and mutual information. 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 807-814(2005).
[6] T F LIU, D Y LIN, W Y LAN. PatchMatch stereo - cross dynamic windows based on textured bithreshold rule, 7382-7387(2023).
[7] S ZAGORUYKO, N KOMODAKIS. Learning to compare image patches via convolutional neural networks, 4353-4361(2015).
[8] J ZBONTAR, Y LECUN. Stereo matching by training a convolutional neural network to compare image patches. Journal of Machine Learning Research, 17, 1-32(2016).
[9] X YE, J LI, H WANG et al. Efficient stereo matching leveraging deep local and context information. IEEE Access, 18745-18755(2017).
[10] A DOSOVITSKIY, P FISCHER, E ILG et al. FlowNet: learning optical flow with convolutional networks., 2758-2766(2015).
[11] N MAYER, E ILG, P HAUSSER et al. A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation, 4040-4048(2016).
[12] J CHANG, Y CHEN. Pyramid stereo matching network, 5410-5418(2018).
[13] G YANG, J MANELA, M HAPPOLD et al. Hierarchical deep stereo matching on high-resolution images, 5515-5524(2019).
[14] A KENDALL, H MARTIROSYAN, S DASGUPTA et al. End-to-end learning of geometry and context for deep stereo regression, 66-75(2017).
[15] X CHENG, Y ZHONG, A HARAKEH et al. Learning stereo matching network with convolutional spatial propagation network, 156-165(2020).
[16] V TANKOVICH, A KAR, C HANE et al. Hitnet: hierarchical iterative tile refinement network for real-time stereo matching, 14362-14372(2021).
[18] K GREGOR, I DANIHELKA, A GRAVES et al. DRAW: a recurrent neural network for image generation, 1462-1471(2015).
[19] J FU, J LIU, H J TIAN et al. Dual attention network for scene segmentation, 3141-3149(2019).
[20] X CHU, W YANG, W L OUYANG et al. Multi-context attention for human pose estimation, 5669-5678(2017).
[21] T XU, P C ZHANG, Q Y HUANG et al. AttnGAN: fine-grained text to image generation with attentional generative adversarial networks, 1316-1324(2018).
[22] V MNIH, N HEESS, A GRAVES et al. Recurrent models of visual attention. 27th International Conference on Neural Information Processing Systems, 2204-2212(2014).
[23] M JADERBERG, K SIMONYAN, A ZISSERMAN et al. Spatial transformer networks. 28th International Conference on Neural Information Processing Systems, 2017-2025(2015).
[25] M MENZE, A GEIGER. Object scene flow for autonomous vehicles, 3061-3070(2015).
[26] K HE, X ZHANG, S REN et al. Spatial pyramid pooling in deep convolutional networks for visual recognition, 346-361(2014).
[27] I GOODFELLOW, Y BENGIO, A COURVILLE et al. Deep Learning(2016).
[28] R GIRSHICK. Fast R-CNN, 1440-1448(2015).
[29] H LAGA, L V JOSPIN, F BOUSSAID et al. A survey on deep learning techniques for stereo-based depth estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44, 1738-1764(2022).
[30] S DUGGAL, S WANG, W C MA et al. DeepPruner: Learning efficient stereo matching via differentiable PatchMatch, 4383-4392(2019).
Get Citation
Copy Citation Text
Tengfei LIU, Dongyun LIN, Weiyao LAN, Yuehang CHEN. PSMNet algorithm based on dual three-pooling attention mechanism[J]. Journal of Applied Optics, 2025, 46(2): 327
Category:
Received: Feb. 1, 2024
Accepted: --
Published Online: May. 13, 2025
The Author Email: Dongyun LIN (林冬云)