Complete contextual information extraction for self-supervised monocular depth estimation
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Published:2024-08
Issue:
Volume:245
Page:104032
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ISSN:1077-3142
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Container-title:Computer Vision and Image Understanding
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language:en
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Short-container-title:Computer Vision and Image Understanding
Author:
Zhou Dazheng, Zhang MingliangORCID, Gao Xianjie, Zhang YoumeiORCID, Li BinORCID
Reference54 articles.
1. LiDARTouch: Monocular metric depth estimation with a few-beam lidar;Bartoccioni;Comput. Vis. Image Underst.,2023 2. Self-supervised deep monocular depth estimation with ambiguity boosting;Bello;IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI),2022 3. Carion, N., Massa, F., Synnaeve, G., Usunier, N., Kirillov, A., Zagoruyko, S., 2020. End-to-End Object Detection with Transformers. In: European Conference on Computer Vision. ECCV, pp. 213–229. 4. Chen, Y., Dai, X., Chen, D., Liu, M., Dong, X., Yuan, L., Liu, Z., 2022. Mobile-Former: Bridging MobileNet and Transformer. In: IEEE Conference on Computer Vision and Pattern Recognition. CVPR, pp. 5270–5279. 5. DeepLab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs;Chen;IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI),2018
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